Dissertations / Theses: 'Agricultural decision support systems'

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Meng, Chao. "Simulation-Based Decision Support For Agricultural Supply Chain Performance Improvement." Diss., The University of Arizona, 2015. http://hdl.handle.net/10150/581318.

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Grafted vegetable seedlings have been proven to possess higher seed/non-seed diseases resistance and yields compared with non-grafted ones. Owing to the seasonality of vegetable planting and labor intensiveness of grafted seedling production (e.g., grafting operation), U.S. vegetable seedling supply chains suffer from high grafted seedling cost. To make grafted seedlings affordable for vegetable growers, low-cost production systems and cost-efficient grafting capacity must be achieved via optimal design of a grafting operation system and supply chain collaboration, respectively. Toward this end, a two-level simulation-based framework is proposed in this work for improving the overall performance of the grafted seedling supply chain by supporting both the grafted seedling production system design and supply chain collaboration decisions. The considered supply chain consists of a single grafted seedling producer that produces grafted seedlings and multiple vegetable growers that seasonally purchase grafted seedlings and produce vegetables to meet price-sensitive demand from the downstream market. More specifically, the low level of the proposed framework focuses on the grafted seedling production system design by integrating discrete event simulation (DES) together with a fuzzy analytic hierarchy process (AHP) for multiple criteria (i.e. production cost, capital investment, production throughput time, resource utilization, and product quality). A Unified Modeling Language (UML)-based simulation modeling and generation approach is developed to automatically generate simulation models of various production system design alternatives. UML information models are developed to provide the system structural information for simulation model generation, production information for simulation execution, and output requirement information for defining simulation outputs. The performance of the production system design alternatives for the aforementioned criteria is evaluated via the generated simulation models, and the corresponding simulation results together with decision makers' judgments on the criteria are used to select the best system design via AHP. A best alternative search (BAS) procedure is proposed for the adopted AHP approach to search for the best system design against ranking impreciseness caused by simulation randomness. At the high level, the proposed framework focuses on the optimal supply chain decisions for early order commitment (EOC) to reduce the amortized production capacity cost. EOC is a supply chain collaboration mechanism, where the grafted seedling producer encourages the vegetable growers to commit their orders earlier than their regular ordering times by providing certain benefits (e.g., price discount). Based on the optimal design of a grafted seedling production system and the corresponding production cost obtained at the low level, we first derive analytical solutions for the grafted seedling producer's optimal capacity, vegetable grower's optimal order quantity, and ordering time under a basic supply chain structure (i.e., single-seedling producer and single-vegetable grower). We then introduce capacity competition by extending the basic structure to a multi-vegetable grower structure. The existence of the N-person game equilibrium and the corresponding relationships between the grafted seedling producer's profit and the vegetable growers' early order decisions are provided. In addition, a capacity reservation mechanism is proposed for the seedling producer to motivate the vegetable growers to release order information in advance. To identify the convergence of the vegetable growers' ordering times, a Cellular Automata simulation model is developed, where each vegetable grower is modeled as a Pavlovian or greedy agent making an ordering time decision so as to receive the higher profit over iterations. The proposed framework is demonstrated for grafted seedling supply chains in North America. The experiment results reveal the benefits of the proposed framework in reducing the grafted seedling cost, as well as in increasing the entire supply chain's profit.

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Fox, Fred Andrew 1956. "Irrigation scheduling decision support." Diss., The University of Arizona, 1997. http://hdl.handle.net/10150/288770.

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Irrigation scheduling using the soil water balance approach has been recommended to irrigators for many years. Reasonably good results are normally obtained by researchers using carefully quantified inputs. Irrigators in production agriculture may estimate inputs and then question the validity of the method when the irrigation recommendations conflict with present irrigation schedules. By associating each input with an interval representing possible bias based on the way the input was estimated, and solving the irrigation scheduling model using the intervals as inputs, the output was associated with an interval representing possible bias. This method was also used to evaluate possible bias associated with growing degree day based crop coefficient curves developed from Arizona crop consumptive use measurements. For comparison purposes, roughly estimated inputs based on irrigation system type, soil type, area weather data and available crop coefficient curves were used as default intervals. Improved input intervals consisted of observed irrigation system performance, soil property measurements, local weather data and theoretical improvements in crop coefficient curves. For surface irrigation, field observation of plant stress and soil water content showed the greatest potential to improve irrigation date predictions. For buried drip under a row crop, accuracy of the predicted daily irrigation rate was most improved by a better estimate of irrigation efficacy.

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Aladenola, Olanike. "Decision support system for irrigation water management." Thesis, McGill University, 2014. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=123181.

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Abstract Variability in seasonal precipitation, potential climate change impacts, competition for water among users, rising population and increasing food demands are putting pressure on agricultural water demands. For irrigated agriculture in Canada to play a major role in addressing current and future global food supply problems, more innovative and sustainable irrigation management approaches are required. In this context a decision support system that ensured more effective irrigation water allocation, application and optimisation was developed. Crop water requirements and irrigation schedules for bell pepper (Capsicum annuum L.) were obtained from greenhouse and field studies. Greenhouse experiments were conducted to determine appropriate irrigation water applications, agronomic and physiological response to water stress for peppers grown on clay and loamy sand soils. These studies involved four irrigation levels -120% (T120), 100% (T100), 80% (T80) and 40% (T40) of pan evaporation (Epan). The results showed that highest yields and water use efficiency were obtained with 120% Epan replenishment on loamy sand compared to clay soil. The corresponding crop water stress index (CWSI) at T120 was 0.18 to 0.20 on clay, and 0.09 to 0.11 on loamy sand. The fruit total soluble solids content was highest in the T40, and least in the T120 treatments.Given that the greenhouse results were obtained under controlled conditions, it was necessary to extend the research in the field. Experiments were conducted to determine the level of available soil water at which irrigation should be applied to prevent water stress and yield loss for peppers on a clay soil. Four irrigation thresholds, as a percentage of available water content, were investigated. These were: 85% (T1), 75% (T2), 50% (T3), and 25% (T4) available water content. A control of no irrigation (T5) was implemented. The crop water stress index (CWSI) and effects of elevated CO2 on the stomatal conductance and water applied were also investigated. The three CO2 levels studied were: ambient CO2 (~400 ppm), predicted CO2 for the year 2050 (550 ppm), and predicted CO2 for the year 2100 (750 ppm). Optimum marketable yields were achieved when 50% (T3) of the available water content had been depleted with a corresponding CWSI of 0.3 to 0.4. A decrease in stomatal conductance with increasing CO2 was observed. Irrigation water requirements decreased by 6-42% under elevated CO2 of 550 ppm, and 28-58% for elevated CO2 of 750 ppm. An integrated agricultural water demand model (IAWDM) was developed using a graphical user interface (GUI) in Matlab to estimate irrigation water requirements (IWR). A pre-requisite for the model development was to ensure that solar radiation (Rs) input data were of good quality. The suitability of nine (Rs) estimation methods, and their effects on reference evapotranspiration (ETo) were evaluated using data from eight weather stations across Canada. Based on Root mean square error (RMSE) of 1-6%, the Hargreaves and Samani (H-S) method gave best results for locations that did not have reliable, long term, observed Rs and sunshine duration data. Output from the IAWDM was compared with CROPWAT simulations, and metered irrigation water-use. IWR from IAWDM deviated from field data by 7 to 28%, while CROPWAT deviated by 7 to 42%. Future IWR was estimated using Agriculture and Agri-food Canada (AAFC) generated climate change data for 2040 to 2069. Results showed that IWR of bell peppers will increase by 19 to 27% in the future. A sensitivity analysis showed that IWR is most sensitive to air temperature, reference evapotranspiration (ETo), and crop coefficients, followed by solar radiation and precipitation.Overall the findings from this study led to a more sustainable greenhouse and field production of vegetable. The improved management practices increased irrigation water use efficiency thereby leading to a more beneficial use of agricultural water.
L'imprévisibilité des présentes précipitations saisonnières et des répercussions potentielles du changement climatique, ainsi que les besoins alimentaires grandissants d'une population croissante, mènent à une compétition plus acharnée entre les utilisateurs des ressources en eau, imposant ainsi d'importantes pressions sur la demande en eau à fins agricoles. Pour que l'agriculture irriguée au Canada puisse contribuer de façon significative à la résolution de présents et futures problèmes d'approvisionnement alimentaire mondial, des modes de gestion d'irrigation plus innovateurs et durables sont nécessaires. Dans ce contexte, un système d'aide à la décision assurant une plus grande efficacité d'allocation, d'application et d'optimisation des eaux d'irrigation fut conçue. Les études en serre établirent un régime d'irrigation approprié pour les poivrons et notèrent leurs réponses agronomiques et physiologiques à des stress hydriques lorsque cultivés sur un sol argileux ou un sable loameux. Quatre niveaux d'irrigation furent évalués, soit 120% (T120), 100% (T100), 80% (T80) ou 40% (T40) de l'évaporation bac (Ebac). Un réapprovisionnement à 120% Ebac entraîna un rendement et une efficacité d'utilisation de l'eau plus élevés sur le sable loameux que sur le sol argileux. L'indice de stress hydrique (ISH) de la culture soumise au taux de réapprovisionnement de 120% fut de 0.18 à 0.20 sur le sol argileux, et de 0.09 à 0.11 sur le sable loameux. Comme les résultats en serre furent obtenus sous des conditions hautement contrôlées, il fut nécessaire d'étendre la recherche à une culture en champ. Une étude fut entreprise sur un sol argileux pour déterminer quel seuil de pourcentage d'eau disponible dans le sol (85%, 75%, 50%, ou 25%) devrait entraîner une irrigation visant à prévenir un stress hydrique du plant de poivron et la perte de rendement qui en suivrait. Un étalon n'ayant reçu aucune irrigation fut également inclus. L'indice de stress hydrique (ISH) fut suivi et l'effet de teneurs élevés en CO2 sur la conductance stomatique et la quantité d'eau devant être appliqué furent également étudiés. Les trois teneurs en CO2 évalués furent celles de l'air ambiant présent (~400 ppm), et les teneurs prédites pour 2050 et 2100 (550 et 750 ppm, respectivement). Un rendement commercialisable optimal fut obtenu avec un seuil d'irrigation représentant à une carence de 50% en eau disponible du sol, ce qui correspond à un indice de stress hydrique de 0.3 à 0.4. Par rapport aux besoins en irrigation sous la présente teneur en CO2 de l'air ambiant, ces besoins diminuèrent de 6 à 42% sous une teneur en CO2 de 550 ppm, et de 28 à 58% sous une teneur en CO2 de 750 ppm. Un modèle intégré de demande en eau pour fins agricoles (MIDEFA) permettant l'estimation des besoins en eau d'irrigation (BEI) fut élaboré en utilisant l'interface graphique de Matlab. L'élaboration du modèle nécessita des données d'entrée de radiation solaire (Rs) de haute qualité. Laquelle de neuf méthodes permettant d'estimer Rs conviendrait le mieux fut évalué en utilisant des données parvenant de huit stations météorologiques canadiennes. Avec une erreur quadratique moyenne de 1 à 6%, la méthode Hargreaves et Samani (H-S) donna les meilleurs résultats. Les données tirées du MIDEFA furent comparées à celles tirées de simulations avec CROPWAT, et aux données provenant d'un compteur d'eau utilisée à fins d'irrigation. Les différences entre le BEI mesuré au champ et ceux calculés par MIDEFA et CROPWAT furent de 7 à 28% et 7 à 42%, respectivement. De futures BEI furent estimés en utilisant des données fournies par Agriculture et Agroalimentaire Canada (AAC), reflétant le changement de climat prévu pour 2040 et 2069. Selon cette analyse, le BEI pour les poivrons augmenterait de 19 à 27% dans l'avenir.Dans l'ensemble les constats de notre étude ont mené à une production de légumes plus durable à la fois en serre et au champ.

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Mackrell, Dale Carolyn, and n/a. "Women as Farm Partners: Agricultural Decision Support Systems in the Australian Cotton Industry." Griffith University. Griffith Business School, 2006. http://www4.gu.edu.au:8080/adt-root/public/adt-QGU20070305.131533.

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Australian farmers are supplementing traditional practices with innovative strategies in an effort to survive recent economic, environmental, and social crises in the rural sector. These innovative strategies include moving towards a technology-based farm management style. A review of past literature determines that, despite a growing awareness of the usefulness of computers for farm management, there is concern over the limited demand for computer-based agricultural decision support systems (DSS). Recent literature indicates that women are the dominant users of computers on family farms yet are hesitant to use computers for decision support, and it is also unclear what decision-making roles women assume on family farms. While past research has investigated the roles of women in the Australian rural sector, there is a dearth of research into the interaction of women cotton growers with computers. Therefore, this dissertation is an ontological study and aims to contribute to scholarly knowledge in the research domain of Australian women cotton growers, agricultural DSS, and cotton farm management. This dissertation belongs in the Information Systems (IS) stream and describes an interpretive single case study which explores the lives of Australian women cotton growers on family farms and the association of an agricultural DSS with their farm management roles. Data collection was predominantly through semi-structured interviews with women cotton growers and cotton industry professionals such as DSS developers, rural extension officers, researchers and educators, rural experimental scientists, and agronomists and consultants, all of whom advise cotton growers. The study was informed by multiple sociological theories with opposing paradigmatic assumptions: Giddens' (1984) structuration theory as a metatheory to explore the recursiveness of farm life and technology usage; Rogers' (1995) diffusion of innovations theory with a functionalist approach to objectively examine the features of the software and user, as well as the processes of technology adoption; and Connell's (2002) theory of gender relations with its radical humanist perspective to subjectively investigate the relationships between farm partners through critical enquiry. The study was enriched further by drawing on other writings of these authors (Connell 1987; Giddens 2001; Rogers 2003) as well as complementary theories by authors (Orlikowski 1992; Orlikowski 2000; Trauth 2002; Vanclay & Lawrence 1995). These theories in combination have not been used before, which is a theoretical contribution of the study. The agricultural DSS for the study was CottonLOGIC, an advanced farm management tool to aid the management of cotton production. It was developed in the late 1990s by the CSIRO and the Australian Cotton Cooperative Research Centre (CRC), with support from the Cotton Research and Development Corporation (CRDC). CottonLOGIC is a software package of decision support and record-keeping modules to assist cotton growers and their advisors in the management of cotton pests, soil nutrition, and farm operations. It enables the recording and reporting of crop inputs and yields, insect populations (heliothis, tipworm, mirids and so on), weather data, and field operations such as fertiliser and pesticide applications, as well as the running of insect density prediction (heliothis and mites) and soil nutrition models. The study found that innovative practices and sustainable solutions are an imperative in cotton farm management for generating an improved triple bottom line of economic, environmental and social outcomes. CottonLOGIC is an industry benchmark for supporting these values through the incorporation of Best Management Practices (BMP) and Integrated Pest Management (IPM) principles, although there were indications that the software is in need of restructuring as could be expected of software over five years old. The evidence from the study was that women growers are participants in strategic farm decisions but less so in operational decisions, partly due to their lack of relevant agronomic knowledge. This hindered their use of CottonLOGIC, despite creative attempts to modify it. The study endorsed the existence of gender differences and inequalities in rural Australia. Nevertheless, the study also found that the women are valued for their roles as business partners in the multidisciplinary nature of farm management. All the same, there was evidence that greater collaboration and cooperation by farm partners and advisors would improve business outcomes. On the whole, however, women cotton growers are not passive agents but take responsibility for their own futures. In particular, DSS tools such as CottonLOGIC are instrumental in enabling women cotton growers to adapt to, challenge, and influence farm management practices in the family farm enterprise, just as CottonLOGIC is itself shaped and reshaped. Hence, a practical contribution of this study is to provide non-prescriptive guidelines for the improved adoption of agricultural DSS, particularly by rural women, as well as increasing awareness of the worth of their roles as family farm business partners.

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Mackrell, Dale Carolyn. "Women as Farm Partners: Agricultural Decision Support Systems in the Australian Cotton Industry." Thesis, Griffith University, 2006. http://hdl.handle.net/10072/365290.

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Australian farmers are supplementing traditional practices with innovative strategies in an effort to survive recent economic, environmental, and social crises in the rural sector. These innovative strategies include moving towards a technology-based farm management style. A review of past literature determines that, despite a growing awareness of the usefulness of computers for farm management, there is concern over the limited demand for computer-based agricultural decision support systems (DSS). Recent literature indicates that women are the dominant users of computers on family farms yet are hesitant to use computers for decision support, and it is also unclear what decision-making roles women assume on family farms. While past research has investigated the roles of women in the Australian rural sector, there is a dearth of research into the interaction of women cotton growers with computers. Therefore, this dissertation is an ontological study and aims to contribute to scholarly knowledge in the research domain of Australian women cotton growers, agricultural DSS, and cotton farm management. This dissertation belongs in the Information Systems (IS) stream and describes an interpretive single case study which explores the lives of Australian women cotton growers on family farms and the association of an agricultural DSS with their farm management roles. Data collection was predominantly through semi-structured interviews with women cotton growers and cotton industry professionals such as DSS developers, rural extension officers, researchers and educators, rural experimental scientists, and agronomists and consultants, all of whom advise cotton growers. The study was informed by multiple sociological theories with opposing paradigmatic assumptions: Giddens' (1984) structuration theory as a metatheory to explore the recursiveness of farm life and technology usage; Rogers' (1995) diffusion of innovations theory with a functionalist approach to objectively examine the features of the software and user, as well as the processes of technology adoption; and Connell's (2002) theory of gender relations with its radical humanist perspective to subjectively investigate the relationships between farm partners through critical enquiry. The study was enriched further by drawing on other writings of these authors (Connell 1987; Giddens 2001; Rogers 2003) as well as complementary theories by authors (Orlikowski 1992; Orlikowski 2000; Trauth 2002; Vanclay & Lawrence 1995). These theories in combination have not been used before, which is a theoretical contribution of the study. The agricultural DSS for the study was CottonLOGIC, an advanced farm management tool to aid the management of cotton production. It was developed in the late 1990s by the CSIRO and the Australian Cotton Cooperative Research Centre (CRC), with support from the Cotton Research and Development Corporation (CRDC). CottonLOGIC is a software package of decision support and record-keeping modules to assist cotton growers and their advisors in the management of cotton pests, soil nutrition, and farm operations. It enables the recording and reporting of crop inputs and yields, insect populations (heliothis, tipworm, mirids and so on), weather data, and field operations such as fertiliser and pesticide applications, as well as the running of insect density prediction (heliothis and mites) and soil nutrition models. The study found that innovative practices and sustainable solutions are an imperative in cotton farm management for generating an improved triple bottom line of economic, environmental and social outcomes. CottonLOGIC is an industry benchmark for supporting these values through the incorporation of Best Management Practices (BMP) and Integrated Pest Management (IPM) principles, although there were indications that the software is in need of restructuring as could be expected of software over five years old. The evidence from the study was that women growers are participants in strategic farm decisions but less so in operational decisions, partly due to their lack of relevant agronomic knowledge. This hindered their use of CottonLOGIC, despite creative attempts to modify it. The study endorsed the existence of gender differences and inequalities in rural Australia. Nevertheless, the study also found that the women are valued for their roles as business partners in the multidisciplinary nature of farm management. All the same, there was evidence that greater collaboration and cooperation by farm partners and advisors would improve business outcomes. On the whole, however, women cotton growers are not passive agents but take responsibility for their own futures. In particular, DSS tools such as CottonLOGIC are instrumental in enabling women cotton growers to adapt to, challenge, and influence farm management practices in the family farm enterprise, just as CottonLOGIC is itself shaped and reshaped. Hence, a practical contribution of this study is to provide non-prescriptive guidelines for the improved adoption of agricultural DSS, particularly by rural women, as well as increasing awareness of the worth of their roles as family farm business partners.
Thesis (PhD Doctorate)
Doctor of Philosophy (PhD)
Griffith Business School
Griffith Business School
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Yule, Ian J. "A decision support system for farm machinery budgeting and selection." Thesis, University of Newcastle Upon Tyne, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.242352.

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Satti, Sudheer Reddy. "GWRAPPS a GIS-based decision support system for agricultural water resources management /." [Gainesville, Fla.] : University of Florida, 2002. http://purl.fcla.edu/fcla/etd/UFE1001180.

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Robinson, Jeffrey Brett, University of Western Sydney, of Science Technology and Environment College, and School of Environment and Agriculture. "Understanding and applying decision support systems in Australian farming systems research." THESIS_CSTE_EAG_Robinson_J.xml, 2005. http://handle.uws.edu.au:8081/1959.7/642.

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Decision support systems (DSS) are usually based on computerised models of biophysical and economic systems. Despite early expectations that such models would inform and improve management, adoption rates have been low, and implementation of DSS is now “critical” The reasons for this are unclear and the aim of this study is to learn to better design, develop and apply DSS in farming systems research (FSR). Previous studies have explored the merits of quantitative tools including DSS, and suggested changes leading to greater impact. In Australia, the changes advocated have been: Simple, flexible, low cost economic tools: Emphasis on farmer learning through soft systems approaches: Understanding the socio-cultural contexts of using and developing DSS: Farmer and researcher co-learning from simulation modelling and Increasing user participation in DSS design and implementation. Twenty-four simple criteria were distilled from these studies, and their usefulness in guiding the development and application of DSS were assessed in six FSR case studies. The case studies were also used to better understand farmer learning through models of decision making and learning. To make DSS useful complements to farmers’ existing decision-making repertoires, they should be based on: (i) a decision-oriented development process, (ii) identifying a motivated and committed audience, (iii) a thorough understanding of the decision-makers context, (iv) using learning as the yardstick of success, and (v) understanding the contrasts, contradictions and conflicts between researcher and farmer decision cultures
Doctor of Philosophy (PhD)

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Qaddoum, Kefaya. "Intelligent real-time decision support systems for tomato yield prediction management." Thesis, University of Warwick, 2013. http://wrap.warwick.ac.uk/58333/.

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This thesis describes the research and development of a decision support system for tomato yield prediction. Greenhouse horticulture such as tomato growing offers an interesting test bed for comparing and refining different predictive modelling techniques. The ability to accurately predict future yields, even for as little as days ahead has considerable commercial value to growers. There are several (measurable) causal variables. Some such as temperature are under the grower's control, while others are not. Modern predictive techniques, based on data mining and self-calibrating models, may be able to forecast future yields per unit area of greenhouse better than the biological causal models implicitly now used by growers. Over the past few decades, it has been possible to use the recorded daily environmental conditions in a greenhouse to predict future crop yields. Existing models fail to accurately predict the weekly fluctuations of yield, yet predicting future yields is becoming desperately required especially with weather change. This research project used data collected during seasonal tomato life cycle to develop a decision support system that would assist growers to adjust crops to meet demand, and to alter marketing strategies. The three main objectives are: firstly, to research and utilize intelligent systems techniques for analysing greenhouse environmental variables to identify the variable or variables that most effect yield fluctuations, and Secondly, to research the use of these techniques for predicting tomato yields and produce handy rules for growers to use in decision-making. Finally, to combine some existing techniques to form a hybrid technique that achieves lower prediction errors and more confident results. There are a range of intelligent systems (IS), which are used to process environment data, including artificial neural networks (ANNs), genetic algorithms (GA) and fuzzy logic (FL). A model providing more accurate yield prediction was developed and tested using industrial data from growers. The author develops and investigates the application of an intelligent decision support system for yield management, and to provide an improved prediction model using intelligent systems (IS). Using real-world data, the intelligent system employs a combination of FL, NN and GA. The thesis presents a modified hybrid adaptive neural network with revised adaptive error smoothing, which is based on genetic algorithm to build a learning system for complex problem solving in yield prediction. This system can closely predict weekly yield values of a tomato crop. The proposed learning system is constructed as an intelligent technique and then further optimized. The method is evaluated using real-world data. The results show comparatively good accuracy.Use was made of existing algorithms, such as self-organizing maps (SOMs), and principal component analysis (PCA), to analyse our datasets and identify the critical input variables. The primary conclusion from this thesis is that intelligent systems, such as artificial neural networks, genetic algorithm, and fuzzy inference systems, can be successfully applied to the creation of tomato yield predictions, these predictions were better and hence support growers’ decisions. All of these techniques are benchmarked against published existing models, such as GNMM, and RBF.

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Lynch, Teresa Ann, and t. lynch@cqu edu au. "Intelligent support systems in agriculture: A study of their adoption and use." Central Queensland University. Computing and Information Systems, 2002. http://library-resources.cqu.edu.au./thesis/adt-QCQU/public/adt-QCQU20040131.101933.

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Australian agriculture is one area in which a number of intelligent support systems have been developed. It appears, however, that comparatively few of these systems are widely used or have the impact the developers might have wished. In this study a possible explanation for this state of affairs was investigated. The development process for 66 systems was examined. Particular attention was paid to the nature of user involvement, if any, during development and the relationship to system success. The issue is not only whether there was user involvement but rather the nature of the involvement, that is, the degree of influence users had during development. The patterns identified in the analysis suggest user influence is an important contributor to the success of a system. These results have theoretical significance in that they add to knowledge of the role of the user in the development of intelligent support systems. The study has drawn together work from three areas: Rogers diffusion theory, the technology acceptance model, and theories relating to user involvement in the development of information systems. Most prior research in the information systems area has investigated one or two of the above three areas in any one study. The study synthesizes this knowledge through applying it to the field of intelligent support systems in Australian agriculture. The results have considerable practical significance, as apparently developers of intelligent support systems in Australian agriculture do not recognize the importance of user participation, and continue to develop systems with less than optimum impact.

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Goden, Mabaya. "Decision Support Systems for Water Environment Management in Rural Areas under Hydrological and Socio-Economic Uncertainties." Kyoto University, 2016. http://hdl.handle.net/2433/217180.

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Kyoto University (京都大学)
0048
新制・課程博士
博士(農学)
甲第20005号
農博第2189号
新制||農||1045(附属図書館)
学位論文||H28||N5014(農学部図書室)
33101
京都大学大学院農学研究科地域環境科学専攻
(主査)教授藤原正幸, 教授村上章, 准教授宇波耕一
学位規則第4条第1項該当

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Heilman, Philip. "A Decision Support System for selecting economic incentives to control nonpoint source pollution from agricultural lands." Diss., The University of Arizona, 1995. http://hdl.handle.net/10150/187172.

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The Southwest Watershed Research Center of the Agricultural Research Service has developed a Prototype Decision Support System (PDSS) which ranks alternative management systems on an individual field based on the returns to the farmer and the quantities of agricultural pollutants leaving the field. A method has been developed which complements the PDSS by extending the analysis to the whole farm, to consider whole farm resource availability as well as aversion to variations in returns and resource availabilities. The method can be used to determine whether or not farmers have the economic incentives needed to induce the adoption of the highly ranked management systems, and if not, the magnitude of the economic incentives needed can be estimated. The method requires the definition of a representative farm, simulating the alternative management systems which are expected to address the major resource problems for which there are insufficient data, scoring those practices with the PDSS, and using an optimization model to determine the set of management systems which is both feasible and maximizes the area weighted score for the farm. This solution represents the socially preferred set of management systems when offsite effects are taken into account. A similar optimization model with a symmetric quadratic formulation is solved to determine the set of management systems a risk averse, profit maximizing farmer would prefer. By comparing the two solutions, the possibility of promoting management systems which can both improve farm income and reduce offsite damage can be determined. The cost to the farmer of adopting the management systems for their offsite benefits can also be estimated. An example for a 243 hectare farm from the deep loess hills in western Iowa was examined to consider farm income, sediment yield, nitrogen and atrazine emissions. The preferred management system from both the farmer's and society's points of view included a corn soybean rotation, no till tillage, and atrazine. Depending on the importance of controlling nitrogen emissions to the decision maker, the cost to the farmer (the required economic incentive) for limiting nitrogen loading to the desired level could reach $10/ha.

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Turner, Aaron P. "DEVELOPMENT OF A DECISION SUPPORT SYSTEM FOR CAPACITY PLANNING FROM GRAIN HARVEST TO STORAGE." UKnowledge, 2018. https://uknowledge.uky.edu/bae_etds/58.

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This dissertation investigated issues surrounding grain harvest and transportation logistics. A discrete event simulation model of grain transportation from the field to an on-farm storage facility was developed to evaluate how truck and driver resource constraints impact material flow efficiency, resource utilization, and system throughput. Harvest rate and in-field transportation were represented as a stochastic entity generation process, and service times associated with various material handling steps were represented by a combination of deterministic times and statistical distributions. The model was applied to data collected for three distinct harvest scenarios (18 total days). The observed number of deliveries was within ± 2 standard deviations of the simulation mean for 15 of the 18 input conditions examined, and on a daily basis, the median error between the simulated and observed deliveries was -4.1%. The model was expanded to simulate the whole harvest season and include temporary wet storage capacity and grain drying. Moisture content changes due to field dry down was modeled using weather data and grain equilibrium moisture content relationships and resulted in an RMSE of 0.73 pts. Dryer capacity and performance were accounted for by adjusting the specified dryer performance to the observed level of moisture removal and drying temperature. Dryer capacity was generally underpredicted, and large variations were found in the observed data. The expanded model matched the observed cumulative mass of grain delivered well and estimated the harvest would take one partial day longer than was observed. Usefulness of the model to evaluate both costs and system performance was demonstrated by conducting a sensitivity analysis and examining system changes for a hypothetical operation. A dry year and a slow drying crop had the largest impact on the system’s operating and drying costs (12.7% decrease and 10.8% increase, respectively). The impact of reducing the drying temperature to maintain quality in drying white corn had no impact on the combined drying and operating cost, but harvest took six days longer. The reduced drying capacity at lower temperatures resulted in more field drying which counteracted the reduced drying efficiency and increased field time. The sensitivity analysis demonstrated varied benefits of increased drying and transportation capacity based on how often these systems created a bottleneck in the operation. For some combinations of longer transportation times and higher harvest rates, increasing hauling and drying capacity could shorten the harvest window by a week or more at an increase in costs of less than $12 ha-1. An additional field study was conducted to examine corn harvest losses in Kentucky. Total losses for cooperator combines were found to be between 0.8%-2.4% of total yield (86 to 222 kg ha-1). On average, the combine head accounted for 66% of the measured losses, and the total losses were highly variable, with coefficients of variation ranging from 21.7% to 77.2%. Yield and harvest losses were monitored in a single field as the grain dried from 33.9% to 14.6%. There was no significant difference in the potential yield at any moisture level, and the observed yield and losses displayed little variation for moisture levels from 33.9% to 19.8%, with total losses less than 1% (82 to 130 kg dry matter ha-1). Large amounts of lodging occurred while the grain dried from 19.8% to 14.6%, which resulted in an 18.9% reduction in yield, and harvest losses in excess of 9%. Allowing the grain to field dry generally improved test weight and reduced mechanical damage, however, there was a trend of increased mold and other damage in prolonged field drying.

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Hanna, Kalim Nabil. "Integrated economic decision support system model for determining irrigation application and projected agricultural water demand on a watershed scale." College Park, Md. : University of Maryland, 2006. http://hdl.handle.net/1903/4153.

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Thesis (Ph. D.) -- University of Maryland, College Park, 2006.
Thesis research directed by: Biological Resources Engineering. Title from t.p. of PDF. Includes bibliographical references. Published by UMI Dissertation Services, Ann Arbor, Mich. Also available in paper.

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Fink, Caleb D. "Developing, Evaluating, and Demonstrating an Open Source Gateway and Mobile Application for the Smartfarm Decision Support System." DigitalCommons@CalPoly, 2018. https://digitalcommons.calpoly.edu/theses/1880.

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The purpose of this research is to design, develop, evaluate, and demonstrate an open source gateway and mobile application for the SmartFarm open source decision support system to improve agricultural stewardship, environmental conservation, and provide farmers with a system that they own. There are very limited options for an open source gateway for collecting data on the farm. The options available are: expensive, require professional maintenance, are not portable between systems, improvements are made only by the manufacturer, limited in customization options, difficult to operate, and data is owned by the company rather than the farmer. The gateway is designed to send data to the cloud from remote SmartFarm Data Acquisition (DAQ) nodes, collect measurement data from remote SmartFarm DAQ nodes, provide a means of wirelessly programming remote SmartFarm DAQ nodes, and a tool that provides data analysis and insight from remote SmartFarm DAQ nodes. It is evaluated to work with 900MHz radios, SmartFarm DAQ nodes, and costs $35. Its setup takes 4 steps and ~20 minutes installation time, does not require maintenance, can utilize Wi-Fi, Bluetooth, and other wireless protocols, and software can port to other systems. The gateway measured data rate of 93.4Mbit/s internet upload speed, passing a range of 252 to 1592 bytes of data from a remote node to the cloud, consumes 2.8 Watts, with a software efficiency of 25% CPU usage, a measurement efficiency of 1 message every 15 seconds, can provide data analysis with the cloud service tool, and it can wirelessly program remote DAQ nodes. The goal of the mobile app is educating farmers, academia, and community members, of farming sustainably today, and for the future. The app is used as a tool to aid people in farming sustainably, teaching agricultural stewardship, and teaching environmental conservation. The app is evaluated with adaptation of 85.1%, frequency of use at 0.12 respondents/minute, and 22 respondents said they find the SmartFarm DSS as beneficial. By developing, evaluating, and demonstrating the gateway and mobile app, the SmartFarm decision support system is a viable option for improving agricultural stewardship and retaining farmers’ ownership of their data.

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Alkimim, Akenya Freire de. "Multicriteria decision analysis applied to the spatial allocation of crops as a planning support system for agricultural expansion in Brazil." Universidade de São Paulo, 2014. http://www.teses.usp.br/teses/disponiveis/11/11140/tde-21032014-112043/.

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The history of the advancement of the agricultural frontier in Brazil has been closely related to environmental losses. Although environmental losses are sometimes inevitable in the context of agricultural expansion, they should always be minimized. This study seeks to avoid the past pattern of development by proposing a more sustainable way of expanding agriculture. The research tests whether it is possible to expand the cultivation of food and fuel crops in Brazil without compromising natural ecosystems. Brazil has a great agricultural potential considering the significant amount of lands that is suitable for agriculture with a favorable climate and topography. To supply the domestic agricultural market and for Brazil to take on a global food and biofuel export leadership position, actions should be taken to plan for this potential sustainable expansion. This planning would be an alternative means of advancing the agricultural frontier, as opposed to the deforestation previously practiced. A way to accomplish a sustainable pattern of agricultural development could be by the identification of suitable areas to support the expansion without further loss of forestlands. Pasture is a type of land use that occupies large areas in Brazil, and pastures are considered strategic resources for the effectiveness of the proposed expansion, given that they represent areas that have already been deforested and offer some type of existing infrastructure. In addition, from the current biophysical potential production - pasture based beef cattle - may be underused. The goal of this dissertation is to develop a spatial allocation model based on a multicriteria decision making and geographic information systems (GIS) using land suitability analysis to support decision makers with geospatial information about where potential areas for sugarcane and soybean expansion are located in Brazil. The multicriteria decision analysis (MCDA) consists of physical land suitability, infrastructure and socioeconomic data integration to identify suitable pasturelands for crop allocation. To enhance the reliability of the model, a team of specialists in the agricultural crops was selected to establish the criteria priorities in the model for the analysis process. The combination of their judgments gives an overall priority that feeds the multicriteria model. \"What if\" scenarios were also built to show how changes in the criteria priority weights would modify the spatial distribution of suitability classes in relation to the main model. The results yield maps that represent the distribution of suitability classes for sugarcane and soybean expansion. Pasturelands become more or less suitable for sugarcane or soybean allocation according to shifts in the influence of each criterion in the model. The designed models show results that may assist policymakers with geospatial information about priority areas where investments and efforts should be directed for sustainable agricultural expansion in Brazil.
A história do avanço da fronteira agrícola no Brasil tem sido intrinsecamente relacionada ao desmatamento. Embora perdas ambientais sejam, por vezes, inevitáveis no contexto de uma expansão agrícola, elas devem ser reduzidas sempre que possível. Tentando não seguir um padrão de desenvolvimento feito à custa de desmatamentos, e pensando numa forma mais sustentável de expansão da agricultura, nós avaliamos nesse estudo a possibilidade de expansão agrícola, para produção de alimentos e de biocombustíveis, sem o comprometimento do ecossistema natural existente no país. O Brasil tem um grande potencial agrícola atribuído à significativa quantidade de solos aptos para agricultura com clima e topografia favoráveis. Para abastecer o mercado agrícola nacional e assumir uma posição de liderança global na exportação de alimentos e biocombustíveis, ações devem ser tomadas pelo Brasil para o planejamento desse potencial de expansão. Esse planejamento seria um modelo alternativo para o avanço da fronteira agrícola, oposto aos padrões de avanço anteriores diretamente relacionados ao desmatamento. Uma forma de conseguir um padrão de desenvolvimento sustentável poderia ser pela identificação de terras agrícolas aptas à essa expansão sem estimular maiores perdas de florestas. As pastagens ocupam grandes áreas no Brasil e são consideradas recursos estratégicos para a eficácia dessa expansão, uma vez que representam áreas que já foram desmatadas e oferecem algum tipo de infraestrutura. Dado o atual potencial biofísico de produção, estima-se que as áreas de pastagem destinadas à pecuária bovina podem estar sendo subutilizadas. O objetivo desse trabalho é desenvolver um modelo de alocação espacial fundamentado numa análise de decisão multicritério e SIG com base na aptidão agrícola das terras, de forma a fornecer informações geoespaciais estratégicas aos tomadores de decisão sobre a localização das áreas potenciais para a expansão da cana-de-açúcar e soja no Brasil. A análise de decisão multicritério (MCDA) consiste na integração de dados edafoclimáticos, de infraestrutura e socioeconômicos para a identificação das áreas de pastagens aptas para a alocação dessas culturas. Para aumentar a confiabilidade do modelo, uma equipe de especialistas em cana-deaçúcar e soja foi selecionada para julgar a prioridade das variáveis no processo de análise. A combinação dos julgamentos fornece uma prioridade geral das variáveis, as quais alimentam o modelo. \"E se\" cenários foram também elaborados para mostrar como as mudanças nos pesos dos critérios modificariam a distribuição espacial das classes de aptidão com relação ao modelo principal. Os resultados são exibidos através de mapas que representam a distribuição das classes de aptidão agrícola para a alocação dos cultivos da cana-de-açúcar e soja. As pastagens tornam-se tanto mais adequadas para a alocação da cana ou soja de acordo com as mudanças na influência de cada critério no modelo. Os modelos projetados mostram resultados favoráveis que podem ajudar os tomadores de decisão com informações geoespaciais que identificam áreas prioritárias onde investimentos e esforços deveriam ser direcionados para estimular a expansão agrícola sustentável no Brasil.

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Passuello, Ana Carolina. "Development of environmental tools for the management of sewage sludge on agricultural soils." Doctoral thesis, Universitat Rovira i Virgili, 2011. http://hdl.handle.net/10803/31940.

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The application of sewage sludge from wastewater treatment plants on agricultural soils has become an increasing practice in recent years, derived from its environmental benefits (recycling of organic matter and nutrients). However, there are a few studies regarding the risks and benefits for both the environment and the human health, probably because of the complexity of the problem and the high stakeholders’ expectations. The objective of this thesis was to develop methodological tools to support the management of sewage sludge on agricultural soils. Fate, human exposure and health risk models were developed, evaluated and integrated. Furthermore, decision models were built up and integrated into Geographic Information System (GIS) so as to indicate the best agricultural areas to amend with sewage sludge. The use of these tools provides more confident decisions regarding this practice.
La aplicación de lodos residuales de depuradora en suelos agrícolas se ha convertido en una práctica cada vez más extensa en los últimos años, derivada de sus beneficios ambientales. Sin embargo, hay pocos estudios sobre los riesgos y beneficios tanto para el medio ambiente como para la salud humana, probablemente debido a la complejidad del problema y las altas expectativas de los participantes en la toma de decisiones. El objetivo de esta tesis fue desarrollar métodos para la gestión de lodos de depuradora en suelos agrícolas. Se desarrollaron, evaluaron e integraron modelos de transporte, exposición humana y riesgos para la salud. Así mismo, se construyeron modelos de decisión y se integraron en Sistemas de Información Geográfica (SIG) para indicar las mejores zonas agrícolas donde aplicar lodos de depuradora. El uso de estas herramientas proporciona decisiones más fiables con respecto a esta práctica.

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Subsorn, Panida. "An investigation into short term latex pricing and national production forecasting decision support system for the public agricultural rubber industry in Thailand." Thesis, Edith Cowan University, Research Online, Perth, Western Australia, 2010. https://ro.ecu.edu.au/theses/1834.

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Decision support systems (DSS) are used to support efficient and effective decision making in many circumstances such as forecasting, managing problems and analysing data. Although used globally in the agricultural, public, government and business sectors, DSS are yet to be adopted within the public agricultural rubber industry in Thailand (PARIT). As PARIT is a significant economic growth area in Thailand, it provides an applied setting for this study; a setting in which the objectives of the National Economic and Social Development Plan (Issue 10) for Thailand must apply. PARIT’s policy makers rely upon basic traditional statistical methods at present. If implemented, more modern forecasting techniques will offer better forecasts and facilitate innovation within PARIT. After an extensive literature survey, this study utilised time series forecasting and DSS with artificial intelligence (AI) to produce an exemplar model for possible adaptation and application within PARIT. Experimentation was conducted to produce a proposed rubber latex price and national rubber production forecasting model which was based upon readily-available rubber data and software. Two techniques were utilised during the experimentation, namely non-neural and neural network (NN) training techniques. The experimentally-derived forecasts were compared with actual rubber latex price and national rubber production data to derive the best-fitting forecasting model. The study confirmed that the non-NN training technique provided more accurate rubber latex price forecasts, as this technique was better able to deal with data sets with high levels of seasonal fluctuations. By contrast, the NN training technique was found to deliver more accurate national rubber production forecasts because there was little data fluctuation to cause errors or ‘noise’. This indicates that forecasts based on the NN training technique will be useful for implementation by policy makers in PARIT. This proposed methodology can be recommended as a practical decision support tool for PARIT. However, the applications of particular forecasting techniques, and the findings from this study, are specific to PARIT. Further research over a longer period of time will be needed to judge more clearly how this forecasting model might be implemented in a wider range of agricultural industry sectors in Thailand and elsewhere.

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Burgess, Robin. "The development of a single strategy for the integration of quantitative and qualitative data types for the production of decision support systems." Thesis, University of Nottingham, 2008. http://eprints.nottingham.ac.uk/14185/.

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The research described in this thesis expresses the importance of quantitative and qualitative data types and how these can be incorporated and combined to produce an agricultural management decision support system (DSS). Researchers cannot solely depend on numerical data and relationships when designing, modelling and producing decision management tools. The relevance of the social sciences and peoples interpretations of these tools is equally important. The DSS described here focuses on the management of rainwater harvesting (RWH) in Tanzania. Numerical data related to natural resources (water and nutrients) and yields of rice and maize have been collected for the production of the DSS. With regard to the social science factors, the DSS tackles the concept of common pool resources (CPR) of water and nutrients. The importance of CPR is well understood, however their inclusion in the production of models is a relatively new concept. Criteria related to social status is linked with the by laws that govern the allocation of natural resources in Tanzania to help derive a numerical method for including CPR within the DSS. The production of the DSS is a novel way of combining this research into a tool that aims to benefit all socio-economic community groups. During the production of the DSS, a single generic approach for the inclusion of quantitative and qualitative information has developed. Particular focus was on the development of a model base (programming and mathematical relationship building), database (storage of the data used for the relationships) and a dialog system (the user-interface and communication strategy). This method is termed the ‘dialog, data, and models (DDM)’ paradigm (Sprague and Carlson, 1982). From this research, a DSS has been produced that aims to optimise RWH management in Tanzania with the aim of alleviating poverty and enhancing sustainable agriculture for all community members. Also an overall strategy for the production of DSSs has been produced. It illustrates how both quantitative (numerical and physical data) and qualitative (socio-economic considerations) can be utilised individually and in combination for the production of DSSs and can be extrapolated for further research and to new areas.

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20

Bujatzeck, Baldur. "Decision support system for alleviating phosphorus contamination." Thesis, McGill University, 2008. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=22032.

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The management of natural resources has greatly improved over the past decade. Despite advances in modelling the fate of nutrients or in modelling socio-economic effects of different farm management strategies, tools that integrate the advances made in these fields are still lacking. To develop a tool to overcome this gap, this research focused on the development of a multi-objective decision support system (MODSS) to alleviate phosphorus (P) contamination from agricultural fields and small watersheds. A decision supporting framework was designed to allow technical and public users to run the MODSS. The MODSS consists of the following elements: nonpoint source pollution models, an expert system to analyse the output of a qualitative P model, a scenario creation routine, a routine to estimate percentage and load based P reduction, a cost/benefits routine and a trade off analysis routine. Throughout the development of the MODSS, it was necessary to design a modified P Index for Southern Quebec. During the design process, the risk class 'controlled subsurface drainage' was introduced into the parameter subsurface drainage. The risk class was included due to findings that suggested that subsurface drainage is an important pathway for P loss in Southern Quebec. The modified P Index was coupled with a pre-screening routine to shorten the P Index analysis. The MODSS was applied to the Castor watershed, Quebec, Canada. The analysis showed that contributing distance, modified connectivity and P application rates are most likely probable causes for P movement from the fields in the Castor watershed. Additionally, the analysis showed that if BMP to reduce P loss are adopted the farmers could generate a surplus income.
La gestion des ressources naturelles s'est considérablement améliorée pendant la décennie passée. Malgré les avances dans la modélisation du destin des nutriants ou dans le domaine de modélisation des effets socio-économiques de différentes stratégies de gestion agricole, il nous manque toujours les outils d'intégrer les avances dans ces domaines. Afin de créer un outil d'integration de ces avances, cette recherche s'est concentrée sur le développement d'un système de soutien à la décision à objectifs multiples pour alléger la contamination de phosphore (P) à partir des champs agricoles et des petites lignes de partage. Le système inclut une interface de soutien à la décision permettant aux utilisateurs techniques et au grand public d'utiliser le MODSS. Le MODSS est composé des éléments suivants: plusieurs modèles de pollution diffuse, un système spécialisé pour analyser le produit de sortie d'un modèle de phosphore qualitatif, une routine de création de scénario, une routine pour estimer la réduction du phosphore en termes de pourcentage et de charge, une routine d'analyse avantages-coûts et une routine d'analyse d'échanges. Le développement du MODSS nécessitait la proposition d'un index du phosphore adapté au sud du Québec. Une nouvelle classe de risques a été introduite dans le paramètre de drainage souterrain: le drainage souterrain contrôlé. Cette classe de risques a été ajoutée, puisque des résultats de recherche extérieurs suggéraient que le drainage souterrain constitue une voie importante de perte du phosphore dans le sud du Québec. L'index modifié du phosphore a été couplé avec une routine d'examens préliminaires afin de raccourcir l'analyse. Le MODSS a été appliqué au bassin-versant de Castor au Québec, Canada. L'analyse a démontré les causes probables du mouvement de phosphore provenant des champs du bassin-versant de Castor : la distance par rapport au point d'origine, la connectivité$

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Petroski, Luiz Pedro. "Uma arquitetura para integração de ambientes data warehouse, espacial e agricultura de precisão." UNIVERSIDADE ESTADUAL DE PONTA GROSSA, 2017. http://tede2.uepg.br/jspui/handle/prefix/143.

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Made available in DSpace on 2017-07-21T14:19:30Z (GMT). No. of bitstreams: 1 Luiz Pedro Petroski.pdf: 3583708 bytes, checksum: cb0543041adedd80936d37a0c95d78ba (MD5) Previous issue date: 2017-03-06
Coordenação de Aperfeiçoamento de Pessoal de Nível Superior
The aim of this work is to present a proposal of integration between Precision Agriculture, DataWarehouse / OLAP and GIS. The integration should use extensible and open components, agricultural modeling for decision support, geographical data support, communication interface between components, extension of existing GIS and Data Warehouse solutions. As a result of the integration, an open and extensible architecture was defined, with a spatial agricultural data warehouse modeling. In this way the technologies and tools are open and allow the implementation and extension of its functionalities to adapt to the agricultural scenario of decision. In order to perform the integration, the data were obtained from a farm in the city of Piraí do Sul/PR, which uses proprietary software for data management. Data was exported to the SHAPEFILE format, and through the process performed by the ETL tool, was extracted, transformed and loaded into the analytical database. Also as a source of political boundaries data of rural regions of Brazil, data from the IBGE were used. The database was modeled and implemented by PostgreSQL DBMS with the extension PostiGIS to support spatial data. To provide the OLAP query service, was used the Geomondrian server. The application was extended from the Geonode project, where it was implemented Analytic functionalities, and the interface between the application and the OLAP was performed by the Mandoline API and the OLAP4J library. And finally the interface was implemented through javascript libraries for creating charts, tables and maps. As principal result, an architecture was obtained for Data Warehouse integration, OLAP operations, agricultural and spatial data, as well as ETL process definition and the user interface.
O objetivo desta dissertação é apresentar uma proposta de integração entre agricultura de precisão, Data Warehouse/OLAP e SIG. A integração deve utilizar componentes abertos e extensíveis, modelagem agrícola para suporte a decisão, suporte a dados geográficos, interface de comunicação entre os componentes e a extensão de soluções existentes de SIG e Data Warehouse. Como resultado da integração foi definido uma arquitetura aberta e extensível, integrada, com uma modelagem de Data Warehouse agrícola espacial, que permite o suporte a tomada de decisão para o planejamento e gestão do manejo das práticas da agricultura de precisão. Desta forma as tecnologias e ferramentas utilizadas são abertas e permitem a implementação e extensão de suas funcionalidades para adequar ao cenário agrícola de tomada de decisão. Para realizar a integração foi utilizado os dados oriundos de uma fazenda localizada em Piraí do Sul/PR, a qual utiliza um software proprietário para o gerenciamento de dados. Os dados foram exportados para o formato SHAPEFILE, e através do processo realizado pela ferramenta de ETL, foram extraídos, transformados e carregados para a base de dados analítica. Também como fonte de dados sobre as fronteiras políticas das regiões rurais do Brasil, foi utilizado dados do IBGE. A base de dados analítica foi modelada e implementada em um SGBD PostgreSQL com a extensão PostiGIS para suportar os dados geográficos. Para prover o serviço de consultas OLAP, foi utilizado o servidor Geomondrian. A aplicação foi estendida do projeto Geonode, onde foi implementado as funcionalidades analíticas, e a interface entre a aplicação e o servidor OLAP, foi realizada pela API Mandoline e a biblioteca OLAP4J. E por fim a interface foi implementada por meio de bibliotecas javascript para a criação de gráficos, tabelas e mapas. Como principal resultado, obteve-se uma arquitetura para integração de datawarehouse, operações OLAP, dados espaciais e agricultura, bem como definição do processo de ETL e a interface com o usuário.

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Kivumbi, Dorian. "Decision support system for improved irrigation water management." Thesis, University of Southampton, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.301207.

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Giboshi, Monica Luri. "Sistema de apoio ao processo de decisão para a gestão do uso agricola da terra." [s.n.], 2005. http://repositorio.unicamp.br/jspui/handle/REPOSIP/257241.

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Orientadores: Luiz Henrique Antunes Rodrigues, Francisco Lombardi Neto
Tese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Agricola
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Resumo: Este trabalho teve como objetivo o desenvolvimento de um sistema de apoio à decisão para a gestão da terra, integrando um Sistema Especialista para determinar a capacidade de uso da terra e outro para recomendar usos adequados e as práticas de conservação e manejo do solo, um Sistema de Informações Geográficas (SIG), uma base de dados e uma interface para interpretar a entrada de dados do usuário e as mensagens passadas entre os sub-sistemas. Todos os diálogos entre o usuário e o sistema são realizados pela da interface, assim como a comunicação entre os componentes do sistema desenvolvido. Os sistemas especialistas foram desenvolvidos utilizando o ¿shell¿ conhecido como CLIPS (C Language Integrated Production System) que provê um ambiente para a construção de sistemas especialistas. O SIG utilizado foi o IDRISI, versão 32, que possui o módulo Applications Programming Interface - API (Interface de Programação de Aplicativos) com um OLE Automation Server, possibilitando o uso de linguagens de alto nível, tais como Visual Basic, para controlar as operações do Idrisi32. A base de dados foi desenvolvida com a utilização do Microsoft Access®, além disso, é de fácil acesso, pois a maioria dos usuários tem esse aplicativo instalado em seus computadores. O sistema desenvolvido determina a capacidade de uso da terra; recomenda usos adequados para cada classe de capacidade de uso; recomenda práticas de conservação e manejo do solo; e identifica áreas de conflito comparando os mapas de uso da terra da região em estudo com o mapa de capacidade de uso. Todos os resultados podem ser visualizados em janelas do programa, gravados ou impressos em formas de relatórios. A validação do sistema foi feita comparando as saídas do sistema com os resultados obtidos de quatro especialistas. As divergências encontradas mostraram que o sistema desenvolvido foi mais rigoroso, principalmente no que diz respeito ao risco de erosão, determinando classes de capacidade de uso diferentes das determinadas por alguns especialistas. Quanto ao tipo de uso e às práticas de conservação e manejo do solo, foram poucas as divergências encontradas. A área utilizada para testar o sistema é o Município de Santo Antônio do Jardim - SP. O sistema classificou 36,95% das terras do município como adequadas para a utilização com cultura anual ou perene; 42,69% são adequadas para pastagem e reflorestamento e 19,51% devem ser utilizadas para preservação ambiental. Outro resultado apresentado é o mapa de intensidade de uso, no qual pôde se observar que 48,50% do município está sendo utilizada de forma adequada; 31,82% com uso inadequado e, 14,06% apresenta subutilização. O sistema mostrou ser uma ferramenta poderosa e eficaz, permitindo avaliar uma região, dando suporte para uma tomada de decisão mais fundamentada
Abstract: The objective of this work was to develop a decision support system for agricultural land environmental planing, which integrates an Expert System to determine the land capability and other to recommend adequate uses and practices for soil conservation and management, Geographic Information System (GIS), a database and an interface to monitor input and output data and the messages passed between the subsystems. The management of all the system is made by an interface developed in Visual Basic, version 5.0. All the dialogues between the user and the system as well as the communication with the components of the system are made through the interface that shows windows, menus, dialog boxes, maps and reports in the screen. It saves the results in files and prints them. The expert systems were developed with a shell known as CLIPS (C Language Integrated Production System), that provides an environment for building expert systems. The GIS was IDRISI, version 32, that has Applications Programming Interface ¿ API with an OLE Automation Server, and makes possible to use high-level languages, such as Visual Basic for controlling the operation of Idrisi32. The database was developed with the Microsoft Access®, because of the majority of the users have this software installed in its computers. The developed system determines land capability from information stored in the database and, also supplied for the SIG, through the soil and slope maps; it recommends adequate uses for land capability class; it recommends practices for soil conservation and management and identifies conflict areas comparing the maps of land use with the land capability. All the results can be visualized by the user through windows of the program, recorded or printed in forms of reports. The validation of the system was done comparing the system outputs with the results obtained of four experts. The divergences have shown that the system was more rigorous than the experts, specially concerning the erosion risk, leading to different land capability classes from those determined for some experts, in some cases. Concerning to the type of practices for soil conservation and management, the divergences have been few. In order to test the system, the county of Santo Antônio do Jardim ¿ SP was selected. The system classified 36.95% of lands as adequate for the use with annual or perennial cultures; 42.69% are adequate for pastures and reforestation and 19.51% must be used for environmental preservation. Another presented result is the map of intensity use, through which could be observed that 48.50% of the lands are being used of adequate form; 31.82% of the lands presents inadequate use and, 14.06% presents under utilization. The system is a powerful and efficient tool, what makes it possible to evaluate a region and give support to a more adequate decision making
Doutorado
Planejamento e Desenvolvimento Rural Sustentável
Doutor em Engenharia Agrícola

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Nguyen, Quang-Duy. "Interoperability and Upgradability Improvement for Context-Aware Systems in Agriculture 4.0." Thesis, Université Clermont Auvergne‎ (2017-2020), 2020. http://www.theses.fr/2020CLFAC017.

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La prochaine évolution de l’agriculture est l’Agriculture 4.0. Dans ce domaine, les nouvelles technologies de l’Internet des Objets (IdO) et les systèmes contextuels sont utilisés pour améliorer les performances des activités agricoles. Un système contextuel est un système capable de réagir automatiquement et adéquatement en fonction du contexte. Le fait d’utiliser un tel système permet non seulement de réduire la charge de travail des agriculteurs, mais aussi d’améliorer la précision des activités agricoles. Cependant, leur emploi dans le monde rencontre deux obstacles spécifiques. Le premier obstacle est le besoin de mettre régulièrement à jour le système contextuel sans changer sa fonctionnalité. Ce besoin s’appuie sur le fait que l’agriculture est une activité saisonnière, avec un lieu de travail externe, ce qui implique plusieurs facteurs imprévisibles qui influent sur les aspects logiciels et matériels du système. Le deuxième obstacle est l’hétérogénéité de données générées à partir du système contextuel. Dans le domaine agricole, on trouve des capteurs variés observant des phénomènes variés et produisant des données également variées. Représenter ces données est un fait nécessaire pour l’interopérabilité des dispositifs à l’intérieur un système contextuel, ou pour l’interopérabilité de plusieurs systèmes contextuels différents à l’intérieur l’écosystème de l’IdO. Cette thèse propose trois contributions. La première est une architecture s’appuyant sur le principe de microservice. Cette architecture est une pile de services pour les systèmes contextuels, qui permet aux développeurs d’un système de se focaliser sur les objectifs des services plutôt que leurs aspects logiciels et matériels. La deuxième contribution est une ontologie, intitulé CASO, dédiée aux systèmes contextuels. Cette ontologie fournit un vocabulaire pour modéliser les données générées par le système contextuel. De plus, elle inclut un mécanisme pour créer des règles de raisonnement. La troisième contribution est un système d’aide à la décision (SAD) pour l’irrigation automatique, développé à partir d’IRRINOV® , une méthode d’irrigation manuelle. Il fait partie d’un système contextuel dédié à l’irrigation de l’équipe TSCF d’INRAE. Ce SAD est basé sur la pile de services pour les systèmes contextuels,et utilise l’ontologie IRRIG, une spécialisation de CASO dédiée à l’irrigation. Les trois contributions vont être appliquées dans un système contextuel d’irrigation déployé dans l’AgroTechnoPôle, situé à Montoldre, en France
The next evolution of agriculture is Agriculture 4.0. Agriculture 4.0 is about using technologies ofthe Internet of Things (IoT) and Context-Aware Systems (CASs) to increase the performance offarming activities. A CAS can react automatically and adequately to the environment based onits context. Applying CASs in agriculture can reduce farm labor and increase the precision offarming activities. However, it encounters two challenges specific to agriculture. The firstchallenge relies on the need to upgrade a CAS regularly with new computing devices orsoftware programs without changing its functionality. Indeed, natural factors, such as violentweather and wild animals, can damage the computing devices located on farmland. Moreover,after each farming season, farmers may need to upgrade their system with new computingdevices and software programs. The second challenge is the data heterogeneity generated froma CAS. In agriculture, various phenomena involve the need to have different sensor devices thatmake numerous types of measurements and produce heterogeneous data. Representing all ofthese heterogeneous data is necessary for the interoperability of different computing devices ina CAS or the interoperability between different CASs in the IoT ecosystem. This thesis proposesthree contributions. The first contribution addresses the first challenge. It is a new architecturebased on the microservice mindset that allows system developers to focus on the services’goals rather than the computing devices and software programs of a CAS. This newarchitecture is called the stack of services for CASs. The second contribution addresses thesecond challenge. It is a new ontology for CASs named CASO. The ontology provides avocabulary to model heterogeneous data generated from CASs and embodies a mechanism tomake rules for reasoning. The third contribution is to build a decision support system (DSS) forthe irrigation CAS in the research unit TSCF, INRAE. The design of the DSS relies on the stackof services for CASs. Moreover, the DSS uses a new ontology called IRRIG, a specialization ofCASO for irrigation. The DSS is an automation version of the manual irrigation methodIRRINOV®. All the guidelines for farmers in IRRINOV® are transformed into rules for reasoning.The contributions of this thesis are going to be applied to build a smart irrigation CAS deployedin AgroTechnoPôle, located in Montoldre, France

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Alkarouri, Muhammad Abdulmuneim. "Distributed decision support systems." Thesis, University of Sheffield, 2010. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.555644.

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Decision support systems are a class of computer based systems that assist in some or all levels of decision making within an organisation. Recently, the growth of data captured that is useful or even critical to the successful running or conclusion of projects in science and industry has been remarkable. Thus, the development of decision support systems that are scalable in terms of the size of data processed. the number of stakeholders, and their geographical span has become of the essence. This thesis identifies the issues in developing distributed decision support systems. Building on that. an architectural style for the development of scalable and extensible software systems is introduced. Subsequently, a framework for the design of distributed decision support systems is developed. This new architectural style is the Resource Oriented Services Architecture (ROSA). It builds on Representational State Transfer (REST), an architectural style that describes the venerable design of the world wide web. An architectural design based on REST revolves around resources, representations, and hyperlinks. \Vhat it lacks is a standardised way to represent computations as resources in a scalable and extensible manner. For systems that cannot be adequately described as a web of documents, this is a shortcoming. ROSA overcomes this by defining a means of representing executable resources in a manner that is consistent with the statelessness and cacheability constraints of REST. The resulting architecture enables the scalability of the system. Additionally, desirable features such as dynamic discovery of resources and extensibility and loose coupling are attained. To illustrate this framework, two new learning algorithms are introduced and implemented as services. The first is a data structure suitable for proximity queries over large datasets of low intrinsic dimension. The other uses a random projection to carry out novelty detection over high dimensional datasets.

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Sandhu, Raghbir Singh. "Intelligent spatial decision support systems." Thesis, University College London (University of London), 1998. http://discovery.ucl.ac.uk/1317911/.

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This thesis investigates the conceptual and methodological issues for the development of Intelligent Spatial Decision Support Systems (ISDSS). These are spatial decision support systems (SDSS) integrating intelligent systems techniques (Genetic Algorithms, Neural Networks, Expert Systems, Fuzzy Logic and Nonlinear methods) with traditional modelling and statistical methods for the analysis of spatial problems. The principal aim of this work is to verify the feasibility of heterogeneous systems for spatial decision support derived from a combination of traditional numerical techniques and intelligent techniques in order to provide superior performance and functionality to that achieved through the use of traditional methods alone. This thesis is composed of four distinct sections: (i) a taxonomy covering the employment of intelligent systems techniques in specific applications of geographical information systems and SDSS; (ii) the development of a prototype ISDSS; (iii) application of the prototype ISDSS to modelling the spatiotemporal dynamics of high technology industry in the South-East of England; and (iv) the development of ISDSS architectures utilising interapplication communication techniques. Existing approaches for implementing modelling tools within SDSS and GIS generally fall into one of two schemes - loose coupling or tight coupling - both of which involve a tradeoff between generality and speed of data interchange. In addition, these schemes offer little use of distributed processing resources. A prototype ISDSS was developed in collaboration with KPMG Peat Marwick's High Technology Practice as a general purpose spatiotemporal analysis tool with particular regard to modelling high technology industry. The GeoAnalyser system furnishes the user with animation and time plotting tools for observing spatiotemporal dynamics; such tools are typically not found in existing SDSS or GIS. Furthermore, GeoAnalyser employs the client/server model of distributed computing to link the front end client application with the back end modelling component contained within the server application. GeoAnalyser demonstrates a hybrid approach to spatial problem solving - the application utilises a nonlinear model for the temporal evolution of spatial variables and a genetic algorithm for calibrating the model in order to establish a good fit for the dataset under investigation. Several novel architectures are proposed for ISDSS based on existing distributed systems technologies. These architectures are assessed in terms of user interface, data and functional integration. Implementation issues are also discussed. The research contributions of this work are four-fold: (i) it lays the foundation for ISDSS as a distinct type of system for spatial decision support by examining the user interface, performance and methodological requirements of such systems; (ii) it explores a new approach for linking modelling techniques and SDSS; (iii) it investigates the possibility of modelling high technology industry; and (iv) it details novel architectures for ISDSS based on distributed systems.

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Argile, Andrew Duncan Stuart. "Distributed processing in decision support systems." Thesis, Nottingham Trent University, 1995. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.259647.

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Woerlee, Auke Peter. "Decision support systems of production scheduling /." Rotterdam : Erasmus universiteit, 1991. http://catalogue.bnf.fr/ark:/12148/cb37438055v.

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Proefschrift--Rotterdam--Erasmus universiteit, 1991.
Mention parallèle de titre ou de responsabilité : Beslissingsondersteunende systemen voor korte termijn produktieplanning. Résumé en néerlandais, 4 p. Ill. par l'auteur. Bibliogr. p. 151-165. Index.

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Hodgkin, Julie. "Provision of intelligent user support in decision support systems." Thesis, University of Strathclyde, 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.366908.

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Kubik, Charles Paul. "Using commercial aviation information systems in operational support airlift decision support systems." Thesis, Monterey, California. Naval Postgraduate School, 2004. http://hdl.handle.net/10945/1397.

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Approved for public release; distribution is unlimited
scheduling solutions for routing aircraft, crews and logistical support needed to successfully operate in this new environment. The opportunity exists for the DoD's private aircraft operation, the Joint Operational Support Airlift Center (JOSAC), to utilize some of the same system features used in commercial operations such as NetJets to improve operations. This thesis will analyze the use of commercial air operator strategies and DSS's to be used in JOSAC to improve operational effectiveness. It will look to add new capabilities and processes used in commercial DSS's along with the implementation of the disruptive technology, microjets. Some of the potential benefits include improved operational performance, solutions to scheduling inefficiencies and improved mission readiness. With these improvements the potential for a military microjet operation in the future is a real possibility.
1st Lieutenant, United States Air Force

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Megeto, Guilherme Augusto Silva 1984. "Avaliação da influência da temperatura e da precipitação na ocorrência da ferrugem asiática da soja por meio da técnica de árvore de decisão." [s.n.], 2012. http://repositorio.unicamp.br/jspui/handle/REPOSIP/256829.

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Orientadores: Stanley Robson de Medeiros Oliveira, Carlos Alberto Alves Meira
Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Agrícola
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Resumo: A ferrugem asiática, causada pelo fungo Phakopsora pachyrhizi, atualmente é considerada uma das doenças mais importantes e agressivas da soja. A principal forma de controle é a aplicação calendarizada de fungicidas a qual desconsidera o risco de ocorrência da doença. Estudos epidemiológicos buscam compreender os fatores que influenciam na ocorrência e desenvolvimento das epidemias, especialmente aqueles relacionados ao ambiente tais como condições meteorológicas. Com o avanço da tecnologia da informação e do armazenamento de dados, técnicas de mineração de dados (data mining) apresentam-se promissoras para a descoberta de conhecimento em bases de dados epidemiológicos. Este trabalho tem como objetivo avaliar a influência da chuva e da temperatura na ocorrência da ferrugem asiática da soja utilizando árvores de decisão. Para tal, foram obtidos dados de ocorrências da doença em quatro safras, de 2007/2008 a 2010/2011, oriundos do banco de dados do Consórcio Antiferrugem, e dados meteorológicos, provenientes do sistema Agritempo. A análise exploratória dos dados permitiu obter subsídios para compor o conjunto de dados final e definir o escopo deste trabalho, buscando-se características intrínsecas à doença e sua interação com o ambiente, utilizando apenas variáveis de base meteorológica. As variáveis utilizadas foram relacionadas à precipitação e à temperatura, que deram origem a nove atributos avaliados para cada período temporal...Observação: O resumo, na íntegra, poderá ser visualizado no texto completo da tese digital
Abstract: The Asian soybean rust, caused by Phakopsora pachyrhizi, is now considered one of the most important and aggressive diseases of soybean. The main form of control is the scheduled application of fungicides which disregards the the risk of disease occurrence. Epidemiological studies seek to understand the factors that influence the occurrence and development of epidemics, especially those related to the environment such as weather conditions. With the development of information technology and data warehousing, data mining techniques appear to be promising for knowledge discovery in epidemiological databases. This study aims to evaluate the influence of rainfall and temperature on the occurrence of soybean rust by using decision trees models. To accomplish that, data of the occurence of the disease were collected from four seasons, 2007/2008 to 2010/2011, from the Consórcio Antiferrugem and weather data from the Agritempo system. Exploratory data analysis allowed for obtaining subsidies to generate the final data set and define the scope of this work, seeking intrinsic characteristics of the disease and its interaction with the environment, using only meteorological variables. The variables used were related to precipitation and temperature, resulting into nine attributes evaluated in different periods. Such attributes were related to the event of occurrence (Oc) and non occurrence (NaoOc) of the disease (assumed as the thirtieth day prior to the event of occurrence). The results include a predictive model and an interpretive model for classifying events of occurrences and non occurrences of the disease...Note: The complete abstract is available with the full electronic document
Mestrado
Planejamento e Desenvolvimento Rural Sustentável
Mestre em Engenharia Agrícola

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Ngimbwa, Peter Cosmas. "An Irrigation Decision Support Tool (IDST) for Smallholdings in Tanzania." The Ohio State University, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=osu1461171005.

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Randall, Todd Andrew. "Decision support for suburban retrofitting /." *McMaster only, 2001.

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Van, Dyk Theron Van Zyl. "Decision support systems for solving discrete multicriteria decision making problems." Master's thesis, University of Cape Town, 1992. http://hdl.handle.net/11427/14300.

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Includes bibliography.
The aim of this study was the design and implementation of an interactive decision support system, assisting a single decision maker in reaching a satisfactory decision when faced by a multicriteria decision making problem. There are clearly two components involved in designing such a system, namely the concept of decision support systems (DSS) and the area of multicriteria decision making (MCDM). The multicriteria decision making environment as well as the definitions of the multicriteria decision making concepts used, are discussed in chapter 1. Chapter 2 gives a brief historical review on MCDM, highlighting the origins of some of the more well-known methods for solving MCDM problems. A detailed discussion of interactive decision making is also given. Chapter 3 is concerned with the DSS concept, including a historical review thereof, a framework for the design of a DSS, various development approaches as well as the components constituting a decision support system. In chapter 4, the possibility of integrating the two concepts, MCDM and DSS, are discussed. A detailed discussion of various methodologies for solving MCDM problems is given in chapter 5. Specific attention is given to identifying the methodologies to be implemented in the DSS. Chapter 6 can be seen as a theoretical description of the system developed, while Chapter 7 is concerned with the evaluation procedures used for testing the system. A final summary and concluding remarks are given in Chapter 8.

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Boyd, Richard K. "A weapons systems development decision support system." Thesis, Monterey, Calif. : Naval Postgraduate School, 1992. http://handle.dtic.mil/100.2/ADA251791.

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Thesis (M.S. in Information Systems)--Naval Postgraduate School, March 1992.
Thesis Advisor: Nakagawa, Gordon. "March 1992." Description based on title screen as viewed on March 4, 2009. Includes bibliographical references (p. 66).

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Goeller, Dale Wellington. "Spreadsheet techniques for logistics decision support systems /." Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 1993. http://handle.dtic.mil/100.2/ADA271846.

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Guo, Yufeng. "Decision support systems for airline crew recovery." [S.l. : s.n.], 2005. http://deposit.ddb.de/cgi-bin/dokserv?idn=976568284.

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Cameron, Mark A., and Mark Cameron@csiro au. "A Problem Model for Decision Support Systems." The Australian National University. Faculty of Engineering and Information Technology, 2000. http://thesis.anu.edu.au./public/adt-ANU20020717.144031.

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This body of research focuses on supporting problem-stakeholders, decision-makers and problem-solvers faced with an ill-defined and complex real world problem. An ill-defined problem has a characteristic trait of continual refinement. That is, the definition of the problem changes throughout the problem investigation and resolution process. The central theme of this research is that a support system should provide problem stakeholders with a problem definition model for constructing and manipulating a representation of the definition of the problem as they understand it. The approach adopted herein is to first develop a problem definition model for ill-defined problems the 6-Component problem definition model. With this model, it is then possible to move on to identifying the types of changes or modifications to the problem definition that problem stakeholders, decision makers and problem solvers may wish to explore. Importantly, there must be a connection between the surface representation of the problem and the underlying implementation of the support system. This research argues that by focusing the support system around the problem definition, it is possible to reduce the mismatch between the problem objectives and the representation of the problem that the support system offers. This research uses the Unified Modelling Language to record and explore the requirements that problem stakeholders, faced with an evolving problem definition, place on a support system. The 6-Component problem definition model is then embedded within a design for an evolutionary support system. This embedding, supported by collaboration diagrams, shows how a system using the 6-Component problem definition model will support stakeholders in their exploration, evaluation and resolution of an ill-defined and complex real-world problem. A case study provides validation of the effectiveness of the 6-Component problem definition model proposed and developed in this work. The case study uses the 6-Component problem definition model as a basis for implementing the Integration Workbench, an evolutionary support system for land-use planning. Stakeholders explore, communicate, evaluate and resolve the Tasmanian Regional Forest Agreement problem with assistance from the Integration Workbench.

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Suen, Fun-sing, and 孫奮生. "Decision support systems for real estate evaluation." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1994. http://hub.hku.hk/bib/B31257021.

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何燦恒。 and Tsan-hang Ho. "Decision support systems in business management games." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1999. http://hub.hku.hk/bib/B31220915.

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Tzavaras, Aris. "Intelligent decision support systems in ventilation management." Thesis, City University London, 2009. http://openaccess.city.ac.uk/12084/.

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Introduction: Intensive Care Unit (ICU) medical personnel, in an ongoing process termed ventilation management, utilize patient physiology and pathology data to define ventilator apparatus settings. Aims: The aim of the research is to develop and evaluate in comparison hybrid ventilation advisor systems, that could support ventilation management process, specific to lung pathology for patients ventilated in control mode. Methodology: A questionnaire was designed and circulated to Intensivists. Patient data, as defined by the questionnaire analysis, were collected and categorized into three lung pathologies. Three ICU doctors evaluated correlation analysis of the recorded data. Evaluation results were used for identifying models basic architecture. Two custom software toolboxes were developed for developing hybrid systems; namely the EVolution Of Fuzzy INference Engines (EVOFINE) and the FUzzy Neural (FUN) toolbox. Eight hybrid systems developed with EVOFINE, FUN, ANFIS and ANN techniques were evaluated against applied clinical decisions and patient scenarios. Results: Seventeen (17) models were designed for each of the eight (8) modeling techniques. The modelled process consisted of twelve physiology variables and six ventilator settings. The number of models’ inputs ranged from single to six based on correlation and evaluation findings. Evaluation against clinical recommendations has shown that ANNs performed better; mean average error as percentage for four of the applied techniques was 0.16%, 1.29% & 0.62 for ANN empirical, 0.05%, 2.23% & 2.30% for ANFIS, 0.93%, 2.33% & 1.89% for EVOFINE and 0.73%, 2.63% & 6.56 for FUN NM, in Normal, COPD and ALI-ARDS categories respectively. Additionally evaluation against clinical disagreement SD has shown that 70.6% of the NN empirical models were performing in 90% of their suggestions within clinical SD, while the percentages were 53%, 53% and 59% for the EVOFINE, ANFIS and NN Normalized models respectively. The EVOFINE and ANFIS produced Fuzzy Systems whose architecture is transparent for the user. Visual observation of ANFIS architectures revealed possibly hazardous advices. Evaluation against clinical disagreement has shown that the NN empirical was not producing hazardous advices, while EVOFINE, ANFIS and NN Normalized were shown to produce potentially hazardous advice in 17.6%, 23% and 5.8% of the developed models.

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Goeller, Dale W. "Spreadsheet techniques for logistics decision support systems." Thesis, Monterey, California. Naval Postgraduate School, 1993. http://hdl.handle.net/10945/39793.

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Approved for public release; distribution is unlimited.
This thesis considers the use of spreadsheet techniques as a foundation for the development of logistics decision support systems. An inventory model is presented to show the flexibility of spreadsheet techniques and demonstrate the use of various graphic

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Anadani, Mohamed. "Decision support systems for nuclear reactor control." Thesis, University of Sheffield, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.341828.

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Jenkins, William Owen. "Decision support systems in river basin management." Thesis, Imperial College London, 1988. http://hdl.handle.net/10044/1/47123.

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Li, Xiaobo 1976. "Decision support systems using object-oriented technology." Thesis, Massachusetts Institute of Technology, 2000. http://hdl.handle.net/1721.1/86539.

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Jackson-Smale, Andrew David. "Intelligent decision support systems for optimised diabetes." Thesis, Oxford Brookes University, 1993. https://radar.brookes.ac.uk/radar/items/cf9b324c-c59f-4b12-b511-1dbe692725f2/1/.

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Computers now pervade the field of medicine extensively; one recent innovation is the development of intelligent decision support systems for inexperienced or non-specialist pbysicians, or in some cases for use by patients. In this thesis a critical review of computer systems in medicine, with special reference to decision support systems, is followed by a detailed description of the development and evaluation of two new, interacting, intelligent decision support systems in the domain of diabetes. Since the discovery of insulin in 1922, insulin replacement therapy for the treatment of diabetes mellitus bas evolved into a complex process; there are many different formulations of insulin and much more information about the factors which affect patient management (e.g. diet, exercise and progression of complications) are recognised. Physicians have to decide on the most appropriate anti-diabetic therapy to prescribe to their patients. Insulin-treated patients also have to monitor their blood glucose and decide how much insulin to inject and when to inject it. In order to help patients determine the most appropriate dose of insulin to take, a simple-to-use, hand-held decision support system has been developed. Algorithms for insulin adjustment have been elicited and combined with general rules of therapy to offer advice for every dose. The utility of the system has been evaluated by clinical trials and simulation studies. In order to aid physician management, a clinic-based decision support system has also been developed. The system provides wide-ranging advice on all aspects of diabetes care and advises an appropriate therapy regimen according to individual patient circumstances. Decisions advised by the pbysician-related system have been evaluated by a panel of expert physicians and the system has undergone informal primary evaluation within the clinic setting. An interesting aspect of both systems is their ability to provide advice even in cases where information is lacking or uncertain.

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Ho, Tsan-hang. "Decision support systems in business management games /." Hong Kong : University of Hong Kong, 1999. http://sunzi.lib.hku.hk/hkuto/record.jsp?B2084301X.

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Suen, Fun-sing. "Decision support systems for real estate evaluation /." Hong Kong : University of Hong Kong, 1994. http://sunzi.lib.hku.hk/hkuto/record.jsp?B25939439.

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Fitz-Rodriguez, Efren. "Decision Support Systems for Greenhouse Tomato Production." Diss., The University of Arizona, 2008. http://hdl.handle.net/10150/195798.

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The purpose of greenhouse crop systems is to generate a high quality product at high production rates, consistently, economically, efficiently and in a sustainable way. To achieve this level of productivity, accurate monitoring and control of some processes of the entire biophysical system must be implemented. In addition, the proper selection of actions at the strategic, tactical and operational management levels must be implemented.Greenhouse management relies largely on human expertise to adjust the appropriate optimum values for each of the production and environmental parameters, and most importantly, to verify by observation the desired crop responses. The subjective nature of observing the plant responses, directly affects the decision-making process (DMP) for selecting these `optimums'. Therefore, in this study several decision support systems (DSS) were developed to enhance the DMP at each of the greenhouse managerial levels.A dynamic greenhouse environment model was implemented in a Web-based interactive application which allowed for the selection of the greenhouse design, weather conditions, and operational strategies. The model produced realistic approximations of the dynamic behavior of greenhouse environments for 28-hour simulation periods and proved to be a valuable tool at the strategic and operational level by evaluating different design configurations and control strategies.A Web-based crop monitoring system was developed for enhancing remote diagnosis. This DSS automatically gathered and presented graphically environmental data and crop-oriented parameters from several research greenhouses. Furthermore, it allowed for real-time visual inspection of the crop.An intelligent DSS (i-DSS) based on crop records and greenhouse environment data from experimental trials and from commercial operations was developed to characterize the growth-mode of tomato plants with fuzzy modeling. This i-DSS allowed the discrimination of "reproductive", "vegetative" and "balanced" growth-modes in the experimental systems, and the seasonal growth-mode variation on the commercial application.An i-DSS based on commercial operation data was developed to predict the weekly fluctuations of harvest rates, fruit size and fruit developing time with dynamic neural networks (NN). The NN models accurately predicted weekly and seasonal fluctuations of each variable, having correlation coefficients (R) of 0.96, 0.87 and 0.94 respectively, when compared with a dataset used for independent validation.

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Ezz, Inas E. "Management support systems integration." Thesis, Brunel University, 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.365077.

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Dissertations / Theses on the topic 'Agricultural decision support systems'

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