Dissertations / Theses on the topic 'Decision-making methods'

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1

Wong, Sandra Sze Man. "Decision making and abortion methods." Thesis, University of Leeds, 2006. http://etheses.whiterose.ac.uk/423/.

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Introduction: This thesis investigates abortion service providers' adequacy to facilitate women's choices to have either a medical or surgical abortion. Both the medical and surgical methods of abortion are effective procedures to terminate unwanted pregnancies in early gestation. Provided there is no medical contraindication, women can make the choice about which method of abortion to have. The role of health professionals is to provide complete and accurate information that encourages women to make informed choices between treatment options. This thesis describes three studies which a) assess the adequacy of written information to support choices about abortion methods across service providers in England and Wales, b) describe the quality of verbal information provided by health professionals to women choosing to have an abortion type in routine consultations, and c) evaluate a leaflet designed to facilitate women's choices to have either a medical or surgical abortion. Methods: Two studies employ a cross-sectional survey design with qualitative and quantitative methods, the third a randomised controlled trial. The samples include: service provider's leaflets from across England and Wales (n=44); the content of doctors' consultations in a regional abortion service in Leeds (n=23); women undertaking abortions for unwanted pregnancies in a regional abortion service in Leeds (n=313). Measures assess the accuracy and quality of information provided, and the degree to which the leaflet facilitated women's decisions about abortion method. Results: The analysis of written and verbal information routinely provided by abortion service providers found that the procedures on having the abortion types were adequately described. However,information about the risks and benefits of each method were described less accurately and/or consistently. The findings from the trial indicate that a leaflet can enable women to make more informed decisions without increasing anxiety but does not impact on the type of abortion method chosen. Conclusions: Most information about types of abortion method routinely provided by abortion service providers is not sufficient to enable women to make informed choices. However, services can meet policy objectives on informed patient decision making with minimal resource implications as the decision aid leaflet enabled women to evaluate more information about the risks and benefits of the abortion methods in accord with their own beliefs.
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Заговора, Ольга Володимирівна, Ольга Владимировна Заговора, and Olha Volodymyrivna Zahovora. "Decision making methods in project management." Thesis, Сумський державний університет, 2013. http://essuir.sumdu.edu.ua/handle/123456789/33556.

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The aim of the article is to demonstrate the importance of the production efficiency increase, and as a result, improvement of product quality. Such efficiency will be provided by implementation of project management methodology. When you are citing the document, use the following link http://essuir.sumdu.edu.ua/handle/123456789/33556
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Gladka, O. M. "Methods of decision-making in projects." Thesis, Sumy State University, 2016. http://essuir.sumdu.edu.ua/handle/123456789/47014.

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The course "Methods of decision-making in projects " reveals the essence of project management through the mechanism of making design decisions. To make design decisions using different approaches: expert techniques Multicriteria methods, methods of group decision-making design decisions under uncertainty, decision making under the project risk.
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4

Hoffman, Matthew William. "Decision making with inference and learning methods." Thesis, University of British Columbia, 2013. http://hdl.handle.net/2429/44083.

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In this work we consider probabilistic approaches to sequential decision making. The ultimate goal is to provide methods by which decision making problems can be attacked by approaches and algorithms originally built for probabilistic inference. This allows us to directly apply a wide variety of popular, practical algorithms to these tasks. In Chapter 1 we provide an overview of the general problem of sequential decision making and a broad description of various solution methods. Much of the remaining work of this thesis then proceeds by relying upon probabilistic reinterpretations of the decision making process. This strategy of reducing learning problems to simpler inference tasks has been shown to be very fruitful in much of machine learning, and we expect similar improvements to arise in the control and reinforcement learning fields. The approaches of Chapters 2–3 build upon the framework of [Toussaint and Storkey, 2006] in reformulating the solution of Markov decision processes instead as maximum-likelihood estimation in an equivalent probabilistic model. In Chapter 2 we utilize this framework to construct an Expectation Maximization algorithm for continuous, linear-Gaussian models with mixture-of-Gaussian rewards. This approach extends popular linear-quadratic reward models to a much more general setting. We also show how to extend this probabilistic framework to continuous time processes. Chapter 3 further builds upon these methods to introduce a Bayesian approach to policy search using Markov chain Monte Carlo. In Chapter 4 we depart from the setting of direct policy search and instead consider value function estimation. In particular we utilize least-squares temporal difference learning to reduce the problem of value function estimation to a more standard regression problem. In this chapter we specifically tackle the use of regularization methods in order to encourage sparse solutions. In Chapters 5–6 we consider the task of optimization as a sequential decision problem. In the first of these chapters we introduce the bandit framework and discuss a number of variations. Then in Chapter 6 we discuss a related approach to optimization utilizing Bayesian estimates of the underlying, unknown function. We finally introduce a novel approach to choose between different underlying point selection heuristics.
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Fitzpatrick, Charles Neil Ayvaz Ümit. "Training methods and tactical decision-making simulations." Monterey, Calif. : Naval Postgraduate School, 2007. http://bosun.nps.edu/uhtbin/hyperion-image.exe/07Sep%5FFitzpatrick.pdf.

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Thesis (M.S. in Modeling Virtual Environments and Simulation (MOVES))--Naval Postgraduate School, September 2007.
Thesis Advisor(s): Sadagic, Amela ; Ciavarelli, Anthony. "September 2007." Description based on title screen as viewed on October 22, 2007. Includes bibliographical references (p. 169-172). Also available in print.
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Ayvaz, Ümit, and C. Neil III Fitzpatrick. "Training methods and tactical decision-making simulations." Thesis, Monterey, California. Naval Postgraduate School, 2007. http://hdl.handle.net/10945/3348.

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Introducing simulation training to ground officers for the first time, within an existing proven curriculum, presents a number of challenges and questions. The proper amount of simulation time to evaluate and train skill sets and how to introduce simulation into an existing curriculum are mostly unknown. We have completed two studies at the Naval PostGraduate School (NPS). The first study examined the length of time and the most appropriate method for introducing simulation training to a user. The second study compared the use of the Close Combat Marines (CCM) Tactical Decision-Making Simulation (TDS) with the traditional method of training decision-making called the Tactical Decision-Making Game (TDG). The TDS and TDG were used in a between-subjects experimental design to examine the viability of each with regard to their ability to evaluate several important military traits. We found that both the TDG and the TDS methods were useful in evaluating a participant's leadership characteristics and decision-making ability. However, only the TDS was capable of evaluating situational-awareness. Our results also address a novel way in which these two approaches could be combined to amplify each other's potential in training of ground officers and military personnel in general.
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Smith, Stephanie Marie. "Understanding decision making with process-tracing methods." The Ohio State University, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=osu1562877539274665.

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Mota, Pedro Jorge Gomes. "Comparative analysis of multicriteria decision making methods." Master's thesis, Faculdade de Ciências e Tecnologia, 2013. http://hdl.handle.net/10362/11263.

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Dissertação para obtenção do Grau de Mestre em Engenharia Electrotécnica e de Computadores
The main objective of this dissertation is to perform a Comparative Analysis of different Multicriteria Decision Making Methods applied to real-world problems, in order to produce relevant information to enable the incorporation of those methods on computational platforms. The current document presents a simple case study concerning a decision support application targeted for a real problem regarding retrofitting alternatives of a building with energy efficiency impact. The application process was started with the selection of two Multicriteria Decision Making Methods guided by a preexisting framework, and resulted in the choice of AHP and PROMETHEE II methodologies. These two methods were then combined with three different decision maker profiles (Conservative, Moderate and Aggressive) created by means of risk assessment profiling techniques for portfolio allocation. Afterwards, the chosen decision criteria were disposed in a Risk Pyramid according to their inherent level of risk regarding project evaluation. A match was then performed between the decision maker profiles and each criterion, so as to define a proper set of weights for the decision criteria and preference functions, with corresponding preference and indifference thresholds. Finally, three different sets of results (one for each decision maker profile) were produced using appropriate software, and a Sensitivity Analysis was performed over the criteria to understand their influence on the solution. The general conclusion of this Comparative Analysis is that the increase in the preference modelling ability of the methods brings up the least expected alternatives as recommendations for the decision maker. Besides, we have concluded that the decision profiles that allocate bigger weights to the riskiest criteria are the ones that produce the more dispersed set of results within each method application and within each decision maker profile.
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Moulton, Bruce David Computer Science &amp Engineering Faculty of Engineering UNSW. "Methods for training people's decision-making judgment: a review." Awarded By:University of New South Wales. Computer Science & Engineering, 2008. http://handle.unsw.edu.au/1959.4/41431.

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The subject of enquiry is the variation seen in the results of a specific set of studies about methods for training people’s judgment. This review attempts to synthesise the studies’ findings, and tests hypotheses about the causes of the variation. Research questions ask if variation is attributable to differences in participant characteristics, different aspects of judgment having been targeted, different tasks having been performed or different training strategies having been used. Relevant literature was reviewed, and studies that reported a method for training an aspect of judgment were selected for further quantitative analysis if at least two groups had been randomly selected from a larger set of human adults, one of which received training that another did not, and where, during the test phase, members of no group had access to tools or resources, performed tasks, or received feedback which members of another group did not. A meta-analysis of statistical data from 39 published studies was conducted. The findings are interpreted as indicating variation in the effect of training is attributable to differences in task type and differences in training strategy. The effect of training is greatest in the studies that have diagnostic tasks (p<0.05). The studies that trained participants with examples have, on average, greater effect sizes than studies that did not (p<0.05). Implications, limitations, and avenues for further research are discussed. It is concluded that the findings indicate that different tasks and different training strategies account for a significant proportion of the variation in training effect seen between the selected studies.
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Poojari, C. A. "Stochastic programming : models, solution methods and applications." Thesis, Brunel University, 2002. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.247549.

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Cook, Edward. "Group Decision-Making." VCU Scholars Compass, 2019. https://scholarscompass.vcu.edu/etd/5928.

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The present work explores improvements in group decision-making. It begins with a practical example using state-of-the-art techniques for a complex, high-risk decision. We show how these techniques can reveal a better alternative. Although we created an improved decision process, decision-makers were apt to protect their own organizations instead of the project. This tendency was reduced over the course of the decision-making process but inspired the first conceptual component of this work. The first concept describes the “Cost of Conflict” that can arise in a group decision, using game theory to represent the non-cooperative approach and comparing the outcome to the cooperative approach. We demonstrate that it is possible for the group to settle on a non-Paretto Nash equilibrium. The sensitivity of the decision-maker weights is revealed which led to the second conceptual portion of this work. The second concept applies social network theory to study the influence between decision-makers in a group decision. By examining the number and strength of connections between decision-makers, we build from intrinsically derived weights to extrinsically derived weights by adding the network influences from other decision-makers. The two conceptual approaches provide a descriptive view of non-cooperative decisions where decision-makers still influence each other. These concepts suggest a prescriptive approach to achieving a higher group utility.
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Allen, Trevor. "Methods of coaching to improve decision making in rugby." Thesis, Link to the online version, 2007. http://hdl.handle.net/10019/328.

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Eusuff, Muzaffar M. "Water resources decision making using meta-heuristic optimization methods." Diss., The University of Arizona, 2004. http://etd.library.arizona.edu/etd/GetFileServlet?file=file:///data1/pdf/etd/azu_e9791_2004_051_sip1_w.pdf&type=application/pdf.

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Siddique, Muhammad. "Fuzzy decision making using max-min and MMR methods." Thesis, Blekinge Tekniska Högskola, Sektionen för ingenjörsvetenskap, 2009. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-3042.

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Fuzzy logic is based on the theory of fuzzy sets, where an object’s membership of a set is gradual rather than just member or not a member. Fuzzy logic uses the whole interval of real numbers between zero (False) and one (True) to develop a logic as a basis for rules of inference. Particularly the fuzzified version of the modus ponens rule of inference enables computers to make decisions using fuzzy reasoning rather than exact. We study decision making problem under uncertainty. we analyze Max-Min method and Minimization of regret method originally developed by Savage and further developed by Yager. We generalize The MMR method by creating the parameterized family of minimum regret methods by using the ordered weighted averaging OWA operators.
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Okstad, Eivind H. "Decision Framework for Well Delivery Processes - Application of Analytical Methods to Decision Making." Doctoral thesis, Norwegian University of Science and Technology, Department of Petroleum Engineering and Applied Geophysics, 2007. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-1497.

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A major portion of unproduced oil and gas resources are located in deep-water areas, often at sea level depths between 1500 and 3000 metres. Development of these fields with conventional technology necessitates increasing costs mainly due to the higher rig- and equipment specification needed. Conventional technology normally implies using a 21" marine riser and a 18 3/4" blowout preventer (BOP) that require heavy rig systems for handling and storage. Larger and more costly rigs in combination with longer time spent on the drilling and completion operations are the main contributions to the increasing cost. Thus, new solutions for cost-effective drilling and completion of deep-water wells have emerged during the recent years as alternatives to conventional technology. Among these new solutions are the big-bore well concepts that are focused on in this thesis.

On the other hand, uncertainty is usually connected to application of new technology. Uncertainty relates both to operational aspects, as well as to the expected production availability of finalized wells. Field development by using a big-bore well concept requires that the expected production rate relies on fewer wells compared to typical conventional well design. Thus, uncertainty needs to be considered carefully, as part of the decision basis.

Given the above challenges, decision makers are seeking appropriate methods and tools to support well engineering and the related decision processes. By combining methods within the area of risk analysis and decision analysis, the relevant properties and characteristics of alternative solutions are linked to the important requirements and decision criteria. Special attention is made to decision-making in project teams, or groups as result of a process. This kind of decision-making is interpreted as the decision process in the current thesis.

The main objective of the PhD project has been to develop a decision framework for deep-water well engineering adapted to the needs of a project team being the decision maker. The main intention is to improve confidence among such decision makers. Indirectly, this should stimulate increased utilization of new and alternative technologies for the drilling and completion of deep-water wells.

The framework includes a decision methodology for assessing the possibilities and limitations of technological options in a decision-making context. The body of the methodology contains the following basic steps: 1) Define the technical decision scope and structure of the well delivery process (WDP), 2) Select the basic well concept, and 3) Conduct the detailed design and approve it. In addition to the new decision methodology, a two-step procedure to guide industry implementation has been developed. This procedure involves the intended user from the early beginning. A case study describes an application of the decision methodology on a hypothetical drilling scenario. The case study also verifies the quality of the selected procedures and validates the methodology.

The combined risk assessment and decision analysis is new to well engineering. Instead of independent risk assessments, the current framework links such assessments directly to the decision processes of well engineering, i.e. to the value chain. It deals with the information of relevance, how assessments should be planned and accomplished, and finally, how the results should best be implemented.

The practical contribution of the framework and its methodology should be proactive support to engineering organizations in their decision processes. Both the quality and efficiency of ongoing decision processes are improved. Feedback from Shell mentioned the usefulness of applying the influence diagram method in the early identification phase of potential well concepts. Being part of the current methodology, this method provides linkages between the detailed factors at an operational level and the values aggregated at a higher managerial decision level.

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Golubeva, Olga. "Foreign Investment Decision-Making in Transition Economies." Doctoral thesis, Stockholms universitet, 2001. http://urn.kb.se/resolve?urn=urn:nbn:se:sh:diva-24749.

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The purpose of this project is to describe and explain the foreign investment decision process in the uncertain and turbulent environment of transition economy. By getting an in-depth understanding of how decision-making works in the environment of transition economy, the study intends to contribute to the development of business administration theory in the area of foreign investment decision-making, particularly its application in the turbulent and uncertain world. Theoretical ‘blocks’, elaborated on the basis of literature study, include the following concepts: the framework of transition economy; initial motivation (or reasons) of companies to make foreign direct investments (FDI); investigation of the investment climate and information collection methods; project evaluation and investment decision criteria; risk assessment factors and risk reduction measures. Transition economy is defined in the study as ‘a non-planned, non-market economy’ where the new emerging market institutions coexist with the bureaucracy and hierarchy inherited from the old administrative system. Investment projects, therefore, should probably be seen as being under institutional influence from both the local (i.e. transition economy) and the Western investor’s home country environments. The empirical data presented in the paper also shows that it is necessary to establish the relevant economic, legal, political and social institutions in order to attract FDI. The study further includes the analysis of the main components and features of transition economies and their influence on FDI decision-making. One of the results of the study is that FDI decision-making in transition economies is largely consistent with different theoretical approaches suggested in the literature. On the other hand, the empirical support obtained for different theoretical approaches is often questionable and opened to alternative interpretations. The presented project suggests that theoretical perspectives do not preclude each other, but rather have a complimentary character. The study attempts to contribute to the mainstream FDI theories through a firm-level approach based on the case studies. Two in-depth case studies are presented in the paper: Ericsson’s direct investments in Russia and Vattenfall’s investments in the Baltic countries. A formal questionnaire based on the parameters of theoretical ‘blocks’ was created and 25 top executives from Ericsson and Vattenfall who participated in FDI decision-making were surveyed. The empirical investigation took place during the period 1997 - 1998 with partial updating of the cases during the year 2000.  The study shows that where companies confront stable environments, investment decision routines and procedures will be less necessary and important than where market uncertainty is high. The strong appreciation of the local business partners for properly done investment calculations increases the importance of capital budgeting in transition economies more than in developed market economies. Besides, traditional investment appraisal methods provide managers with an ‘objective’ or ‘materialistic’ feedback for the decision-making in the rapidly changing uncertain environment. On the other hand, the study emphasises the importance of strategy over financial techniques and argues that FDI decisions in transition economies should be based on methods consistent with the company’s long-term objectives. In case of permanent changes, new approaches as well as better co-ordination of traditional techniques with strategic, political, historical, geographical and cultural issues are required. Ericsson’ s direct investments in Russia are presented in the paper in connection with other factors: the company’s historical involvement in Russia, marketing strategy, human resource development, privatisation and restructuring of the telecommunication sector in Russia, etc. Nordic Electric Power Co-operation (Nordel), the EU’ s decision in 1996 to create an internal electricity market in Europe, Baltic ring study, future plans to privatise the energy companies in the Baltic countries, etc., are the framework to present the second case. An application of project evaluation and risk assessment techniques for broader and more complicated environments shows that investment decision-making is probably as much, if not more, a social, political and cultural technology as an economic one. The study argues then that the rational choice decision-making model often co-exists with alternative models elaborated in social science - limited rationality, political and garbage can. According to the empirical data, the investment decisions are largely based on intuition, business experience and judgement, personal contacts with representatives from the local country, and these investment criteria are inevitable and acceptable in a situation of total chaos and permanent change. The right chosen partner, for example, is one of the major criteria for the success of the investment project in a transition economy. One of the outcomes of this study is that the revitalised form of investment decision-making will differ rather markedly from much of what has gone before: less emphasis on the quantitative aspects of capital budgeting, more on the qualitative aspects of companies and investment environment. The project also argues that determinants, approaches and criteria of investment activity in transition economies are largely consistent with patterns observed in other parts of the world. A few specific environmental conditions of transition economies, however, are shown in the study to affect the pattern of FDI decision-making. The level of turbulence is still different compared to the developed market economies due to uncertainties and unpredictibilities associated with environment of transition economies. Other major differences are the large power distance with authoritarian leadership, strong hierarchy and bureaucracy as well as the vital role of personal contacts in transition economies. It is not clear, however, if these features of transition economies should be seen as inherited from the past communist system or as an alternative way to organise the economic actors through networks, a way that is natural and appropriate for the majority of Asian societies.
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Dunn, Sandra I. "Interprofessional Shared Decision Making in NICU: A Mixed Methods Study." Thèse, Université d'Ottawa / University of Ottawa, 2011. http://hdl.handle.net/10393/19903.

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Background: The process of shared decision making (SDM), a key component of interprofessional (IP) practice, provides an opportunity for the separate and shared knowledge and skills of care providers to synergistically influence the client / patient care provided. The aim of this study was to understand how different professional groups perceive IPSDM, their role as effective participants in the process and how they ensure their voices are heard. Methods: A sequential explanatory mixed methods design was used consisting of a realist review of the literature about IPSDM in intensive care, a survey of the IP team (n=96; RR-81.4%) about collaboration and satisfaction with the decision making process in NICU, semi-structured interviews with a sample of team members (n=22) working in NICU, and observation of team decision making interactions during morning rounds over a two week period. A tertiary care NICU in Canada was the study setting. Findings: The study revealed a number of key findings that are important to our increased understanding of IPSDM. Healthcare professionals’ (HCP) views differ about what constitutes IPSDM. The nature of the decision (triage, chronic condition, values sensitive) is an important influencing factor for IPSDM. Four key roles were identified as essential to the IPSDM process: professional expert, leader, synthesizer and parent. IPSDM involves collaboration, sharing, weighing and building consensus to overcome diversity. HCPs use persuasive knowledge exchange strategies to ensure their voices are heard during IPSDM. Buffering power differentials and increasing agreement about best options lead to well-informed decisions. A model was developed to illustrate the relationships among these concepts. Conclusions: Findings from this study improve understanding of how different members of the team participate in the IPSDM process, and highlight effective strategies to ensure professional voices are heard, understood and considered during deliberations.
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Oscarson, Nils. "Health economic evaluation methods for decision-making in preventive dentistry." Doctoral thesis, Umeå : Public Health and Clinical Medicine, 2006. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-687.

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McAndrew, Claire-Louise. "Cross-fertilising methods in naturalistic decision-making and managerial cognition." Thesis, University of Surrey, 2008. http://epubs.surrey.ac.uk/984/.

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The aim of this thesis is to examine the potential for methodological exchange between the fields of naturalistic decision-making (NDM) and managerial cognition. The research outlined makes a contribution towards methodological choice and research design within these fields. It also contributes by highlighting the theoretical value of applying a naturalistic mode of enquiry to the study of investment professionals. This research is situated in response to a number of calls for inter-disciplinary conversation in the study of cognition (Hodgkinson and Healey, 2008; Hodgkinson and Thomas, 1997; Lipshitz, Klein and Carroll, 2006). As such, it is located within the wider organisational debates of the social, management and behavioural sciences. Building upon the arguable inappropriateness of existing managerial cognition - behavioural decision-making (BDM) collaborations, this thesis advocates a naturalistic approach for progressing understanding of 'real-world' decision-making. In doing so, and in addressing the methodological challenges associated with these fields, the thesis examines the utility of connectionist architectures and structured qualitative approaches for the elicitation and representation of cognition. Three studies progressively examine the boundaries of cross-fertilisation using investment professionals as a backdrop for study. The results suggest inter-disciplinary collaboration to be useful not only in developing the reperto.ire of methodological tools available to the social sciences researcher, but in progressing theoretical thought (ie. through the concepts of coherence and sense-making) and in addressing epistemological debates within these fields. This thesis therefore contributes towards rapprochement of quantitative-qualitative approaches in NDM and computational-interpretative perspectives in the field of managerial cognition by modelling their dynamic interplay. The results also draw attention to the importance of understanding the socially situated aspects of expertise and the value in obtaining a multi-perspective understanding of cognition through mixed-methods designs. This thesis suggests that further collaboration both in a theoretical and methodological sense has much to offer these two fields and is an appropriate avenue for progression.
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Roach, Thomas Peter. "Decision making methods for water resources management under deep uncertainty." Thesis, University of Exeter, 2016. http://hdl.handle.net/10871/25756.

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Substantial anthropogenic change of the Earth’s climate is modifying patterns of rainfall, river flow, glacial melt and groundwater recharge rates across the planet, undermining many of the stationarity assumptions upon which water resources infrastructure has been historically managed. This hydrological uncertainty is creating a potentially vast range of possible futures that could threaten the dependability of vital regional water supplies. This, combined with increased urbanisation and rapidly growing regional populations, is putting pressures on finite water resources. One of the greatest international challenges facing decision makers in the water industry is the increasing influences of these “deep” climate change and population growth uncertainties affecting the long-term balance of supply and demand and necessitating the need for adaptive action. Water companies and utilities worldwide are now under pressure to modernise their management frameworks and approaches to decision making in order to identify more sustainable and cost-effective water management adaptations that are reliable in the face of uncertainty. The aim of this thesis is to compare and contrast a range of existing Decision Making Methods (DMMs) for possible application to Water Resources Management (WRM) problems, critically analyse on real-life case studies their suitability for handling uncertainties relating to climate change and population growth and then use the knowledge generated this way to develop a new, resilience-based WRM planning methodology. This involves a critical evaluation of the advantages and disadvantages of a range of methods and metrics developed to improve on current engineering practice, to ultimately compile a list of suitable recommendations for a future framework for WRM adaptation planning under deep uncertainty. This thesis contributes to the growing vital research and literature in this area in several distinct ways. Firstly, it qualitatively reviews a range of DMMs for potential application to WRM adaptation problems using a set of developed criteria. Secondly, it quantitatively assesses two promising and contrasting DMMs on two suitable real-world case studies to compare highlighted aspects derived from the qualitative review and evaluate the adaptation outputs on a practical engineering level. Thirdly, it develops and reviews a range of new potential performance metrics that could be used to quantitatively define system resilience to help answer the water industries question of how best to build in more resilience in future water resource adaptation planning. This leads to the creation and testing of a novel resilience driven methodology for optimal water resource planning, combining optimal aspects derived from the quantitative case study work with the optimal metric derived from the resilience metric investigation. Ultimately, based on the results obtained, a list of suitable recommendations is compiled on how to improve the existing methodologies for future WRM planning under deep uncertainty. These recommendations include the incorporation of more complex simulation models into the planning process, utilisation of multi-objective optimisation algorithms, improved uncertainty characterisation and assessments, an explicit robustness examination and the incorporation of additional performance metrics to increase the clarity of the strategy assessment process.
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Marto, Marco Henrique Vieira. "Innovating forest ecosystems with advanced multi-criteria decision-making methods." Doctoral thesis, ISA, 2020. http://hdl.handle.net/10400.5/21204.

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Doutoramento em Engenharia Florestal e dos Recursos Naturais - Instituto Superior de Agronomia. Universidade de Lisboa
This work focuses on innovating forest ecosystem management planning and on enhancing its contribution to the provision of ecosystem services. A web-based forest decision support system was developed to support public and private forest managers, involving operational research methods. First, all work related to database management and the integration of data was carried out. Databases were created with PostgreSQL, which on the one hand facilitated the development of multi-criteria linear programs, and on the other met all the data and information needs of a forest decision support system, not only for data processing and information presentation, but also as a source to be consulted and analyzed by forest decision makers. The wSADfLOR, a forest web-based decision support system, integrates one analytic tool to visualize interactive decision maps showing the decision space and trade-offs among the criteria in Pareto frontiers, according to forest users’ management options. Taking advantage of constant improvements in the Interactive Decision Maps tool in wSADfLOR, a second article was developed regarding a web-based approach to show interactive decision maps with Pareto frontiers. Based on these interactive decision maps and jointly with some decision support systems available in the EMDS platform (Criterion DecisionPlus and NetWeaver), a hybrid decision methodology for cases in which there is no consensus among the solutions chosen by different (groups of) forest decision makers was developed, enabling them to choose a unique strategic decision plan
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Burnett, Timika L. Ergun Mehmet. "A decision-making model utilizing information technology : combining the features of the Internet, Public participation and proven decision-making methods /." Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 1999. http://handle.dtic.mil/100.2/ADA376710.

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Thesis (M.S. in Information Technology Management) Naval Postgraduate School, December 1999.
"December 1999". Thesis advisor(s): Gregory Hildebrandt, Matthew S. Feely. Includes bibliographical references (p. 87-89). Also available online.
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Burnett, Timika L., and Mehmet Ergun. "A decision-making model utilizing information technology : combining the features of the Internet, Public participation and proven decision-making methods." Thesis, Monterey, California: Naval Postgraduate School, 1999. http://hdl.handle.net/10945/13417.

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This thesis research combines several proven methods by which public participation can be used more effectively in a government decision-making process. The research involved fulfills three primary purposes. First, the research provides a flexible user-friendly internet-based platform, whereby the knowledge level of a disparate group of stakeholders can be improved with respect to a complex technical subject. Second, the research demonstrates a method by which stakeholder consensus is derived. Third, the research exhibits a method by which public values are aggregated, whatever the level of consensus; the data is then provided to the government for use in a decision-making model.
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24

Sycara, Ekaterini P. "Resolving adversarial conflicts : an approach integrating case-based and analytical methods." Diss., Georgia Institute of Technology, 1987. http://hdl.handle.net/1853/32955.

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25

Ozer, Ibrahim. "Multi-criteria group decision making methods using AHP and integrated Web-based decision support systems." Thesis, University of Ottawa (Canada), 2007. http://hdl.handle.net/10393/27545.

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This thesis explores different group decision making methods using the Analytical Hierarchical Process (AHP) applied to the multi-criteria decision making problem of selecting a preferred "site" and develops a support system for group decision making. The group members consider sites to have alternative and often conflicting uses. It is imperative for decision makers in the responsible group to have an appropriate combination of tools, computer software and decisions support systems in order to make the most preferred decisions as a group despite potential inherent conflict among members of the decision making group. To support this idea and facilitate decision making, alternative group multi-criteria decision making (MCDM) evaluation techniques are examined. These include; AHP, Weighted Sum Method (WSM), Weighted Product Method (WPM), AHP Combined Method, Group Evaluation Method, Fuzzy AHP, Fuzzy AHP Combined, and Fuzzy AHP Group. A web-based comparison framework is developed as a prototype to facilitate model use. These methods are applied to the evaluation of coastal zone sites for alternate marine use including aquaculture or fish farming. Aquaculture is one of the fastest growing activities among coastal nations. At the same time, companies, researchers, and coastal communities are seeking assistance in identifying appropriate coastal zone sites for commercial fishing and aquaculture activities, habitat reserves, and marine recreation. The aquaculture case study evaluates four possible fish sites in the Grand Marian Island area of Atlantic Canada.
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26

Cao, Patrick Pu 1963. "The effects of parallel versus sequential coordination methods on distributed group multiple critera decision-making outcomes : an empirical study with a web-based GDSS prototype." Monash University, School of Information Management and Systems, 2003. http://arrow.monash.edu.au/hdl/1959.1/8107.

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27

Simanavičienė, Rūta. "The sensitivity analysis of the quantitative multiple attribute decision making methods." Doctoral thesis, Lithuanian Academic Libraries Network (LABT), 2012. http://vddb.laba.lt/obj/LT-eLABa-0001:E.02~2012~D_20120227_123130-48460.

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The problems, associated with sensitivity of quantitative multiattribute decision-making methods to the initial data and the reliability of the decision obtained by using these methods, are considered in the presented dissertaition. The methods discussed are applied to solving decision-making problems, consisting in the selection of one alternative out of the available several options, when a decision-making person seeks to achieve a number of aims, rather than a single aim, and the alternatives are evaluated based on a set of attribute, which may be conflicting. The research object is sensitivity of the popular quantitative multiattribute decision-making methods: TOPSIS, SAW and COPRAS to the initial data errors. The initial data inaccuracy may be caused by the errors made by a person, entering the data. The estimates of the alternatives may have some errors, which are not taken into account, when the considered methods are used with these data. The analysis of the related works has shown that there are methods for evaluating sensitivity with respect to one attribute, based on varying the significance values, such as the method of the most critical criterion (Triantaphyllou 2000) and to many attributes - Tornado diagram. However, these methods do not show either the errors of solution results or the reliability level of the result obtained. The main aim of the dissertation is the evaluation of the stochastic nature of multiattribute decision-making methods, based on... [to full text]
Disertacijoje nagrinėjamas kiekybinių daugiatikslių sprendimo priėmimo metodų jautrumas ir juos taikant gautų sprendimų patikimumas. Daugiatiksliai sprendimo priėmimo metodai taikomi sprendimo priėmimo uždaviniuose, renkantis vieną alternatyvą iš keleto galimų, kai sprendimą priimantis asmuo siekia ne vieno, o kelių tikslų, o alternatyvos vertinamos pagal daugelį efektyvumo rodiklių, kurie gali būti tarpusavyje prieštaraujantys (pvz. kainos ir naudos rodikliai). Pagrindinis tyrimo objektas yra metodų TOPSIS, SAW ir COPRAS jautrumas pradinių duomenų netikslumams. Duomenų netikslumai galimi dėl pradinių duomenų reikšmes nustatančio asmens padarytų klaidų. Tokiu atveju, kai taikant minėtus metodus, alternatyvų vertinimui naudojami pradiniais duomenys turintys tam tikras paklaidas, alternatyvų vertinimai gali būti su paklaidomis, kurios, taikant šiuos metodus, nebėra vertinamos. Išanalizavus susijusius darbus, nustatyta, jog yra metodų, skirtų vertinti sprendimo jautrumą vieno rodiklio atžvilgiu, keičiant reikšmingumo reikšmes, tai - kritiškiausio kriterijaus metodas (Triantaphyllou 2000) ir daugelio rodiklių atžvilgiu - Tornado diagrama. Tačiau šie metodai nepateikia nei sprendimo rezultatų paklaidų, nei rezultato patikimumo laipsnio. Pagrindinis disertacijos tikslas – įvertinti daugiatikslių, kiekybiniais matavimais pagrįstų sprendimo priėmimo metodų stochastiką. Sukurtų metodų taikymo sritis – sprendimo paramos sistemų projektavimas, sprendimų patikimumo ir sprendimų priėmimo... [toliau žr. visą tekstą]
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28

Amini, Mohammadhossein. "A study of multiple attributes decision making methods facing uncertain attributes." Thesis, Kansas State University, 2015. http://hdl.handle.net/2097/20542.

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Master of Science
Department of Industrial & Manufacturing Systems Engineering
Shing I. Chang
Many decision-making methods have been developed to help decision makers (DMs) make efficient decisions. One decision making method involves selecting the best choice among alternatives based on a set of criteria. Multiple Attribute Decision-Making (MADM) methods allow opportunities to determine the optimal alternative based on multiple attributes. This research aims to overcome two concerns in current MADM methods: uncertainty of attributes and sensitivity of ranking results. Based on availability of information for attributes, a DM maybe certain or uncertain on his judgment on alternatives. Researchers have introduced the use of linguistic terms or uncertain intervals to tackle the uncertainty problems. This study provides an integrated approach to model uncertainty in one of the most popular MADM methods: TOPSIS (Technique for Order Preference by Similarity to Ideal Solution). Current MADM methods also provide a final ranking of alternatives under consideration and, the final solution is based on a calculated number assigned to each alternative. Results have shown that the final value of alternatives may be close to each other uncertain attributes, but current methods rank alternatives according to the final scores. It exhibits a sensitivity issue related to formation of the ranking list. The proposed method solves this problem by simulating random numbers within uncertain intervals in the decision matrix. The proposed outcome is a ranking distribution for alternatives. The proposed method is based on TOPSIS, which defines the best and the worst solution for each attribute and defines the best alternative as closest to best and farthest from the worst solution. Random number distributions were studied under the proposed simulation solution approach. Result showed that triangular random number distribution provides better ranking results than uniform distribution. A case study of building design selection considering resiliency and sustainability attributes was presented to demonstrate use of the proposed method. The study demonstrated that proposed method can provide better decision option for designers due to the ability to consider uncertain attributes. In addition using the proposed method, a DM can observe the final ranking distribution resulted from uncertain attribute values.
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29

Villacampa, Osiris. "Feature Selection and Classification Methods for Decision Making: A Comparative Analysis." NSUWorks, 2015. http://nsuworks.nova.edu/gscis_etd/63.

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The use of data mining methods in corporate decision making has been increasing in the past decades. Its popularity can be attributed to better utilizing data mining algorithms, increased performance in computers, and results which can be measured and applied for decision making. The effective use of data mining methods to analyze various types of data has shown great advantages in various application domains. While some data sets need little preparation to be mined, whereas others, in particular high-dimensional data sets, need to be preprocessed in order to be mined due to the complexity and inefficiency in mining high dimensional data processing. Feature selection or attribute selection is one of the techniques used for dimensionality reduction. Previous research has shown that data mining results can be improved in terms of accuracy and efficacy by selecting the attributes with most significance. This study analyzes vehicle service and sales data from multiple car dealerships. The purpose of this study is to find a model that better classifies existing customers as new car buyers based on their vehicle service histories. Six different feature selection methods such as; Information Gain, Correlation Based Feature Selection, Relief-F, Wrapper, and Hybrid methods, were used to reduce the number of attributes in the data sets are compared. The data sets with the attributes selected were run through three popular classification algorithms, Decision Trees, k-Nearest Neighbor, and Support Vector Machines, and the results compared and analyzed. This study concludes with a comparative analysis of feature selection methods and their effects on different classification algorithms within the domain. As a base of comparison, the same procedures were run on a standard data set from the financial institution domain.
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30

Gollan, Srisuda Siera. "A Mixed Methods Examination of Pre-Hospital Trauma Triage Decision Making." Thesis, Augusta University, 2017. http://pqdtopen.proquest.com/#viewpdf?dispub=10634622.

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The objective of pre-hospital trauma care is ensuring that the most severely injured persons are transported to the facility best suited to meet their complex needs (Fitzharris, Stevenson, Middleton, & Sinclair, 2011; Hoff, Tinkoff, Lucke, & Lehr, 1992; Leach et al., 2008; Sasser et al., 2012). To support pre-hospital decision making regarding trauma triage destination determinations, the Guidelines for Field Triage of Injured Patients decision scheme (FTDS) was developed as an algorithmic decision tool (Sasser et al., 2012).

The purpose of this study was to examine pre-hospital trauma triage transport decision making by EMS providers from multiple perspectives. This study used a concurrent mixed methods triangulation design (QUAL+QUANT). Mixed methods included: (1) Grounded theory methodology to describe a model of decision making used by EMS providers to make trauma triage determinations and (2) quantitative analysis of secondary data to determine how the FTDS criteria are utilized by EMS providers. The FTDS criteria were also examined relative to trauma outcomes: level of trauma team activation (TTA), patient disposition when leaving the emergency department (ED), and the injury severity score (ISS).

A model of Interpreting Trauma into Action was elucidated to describe the processes used by EMS providers. Pre-hospital providers based their trauma transport decisions on the perceived patient level of injury severity. The FTDS criteria were not explicitly used in this study region, but were interwoven into practice through employer policies and other training. The convergence of these findings indicated congruence between the model and trauma outcomes. The quantitative data indicated relationships (p<.05) between 12 of the 29 FTDS criteria and trauma outcomes. Both sources of evidence supported the relationships between the model of Interpreting Trauma into Action, the FTDS criteria, and specific trauma outcomes.

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31

Mansell, Ingrid Jane. "The role of analytics in management decision making within an organisation in the Western Cape, South Africa." Thesis, Cape Peninsula University of Technology, 2016. http://hdl.handle.net/20.500.11838/2472.

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Thesis (MTech (Business Administration))--Cape Peninsula University of Technology, 2016.
This mixed methods study examined specific influences on low usage of analytics among level 4 managers in a selected public sector organisation, based on SAP Business Intelligence (SAP BI) log on statistics collected between July 2012 and June 2016. Analytics provides an organisation the ability to enable its management team to make decisions based on facts, rather than assumption. The aim of this interpretivist research, grounded in a subjectivist epistemological position, was to gain an in-depth understanding of the manager’s environment and how it influences the usage and adoption of analytics in strategic decision making. Human beings change all the time and the environment in which they find themselves constantly influences them. The main research question was: what specific factors inhibit managers’ use of analytics in organisations? A case study approach was deemed the most appropriate for this kind of study because specific environmental factors influence analytics usage. Themes identified as possible factors influencing different dimensions included: individual characteristics, business intelligence systems quality, organisational factors, macro-environment factors, behavioural beliefs and attitudes, effort perceptions, social influence, facilitating conditions and other. For the qualitative component, eight level 4 public sector managers within the selected organisation were interviewed in order to experience the work environment and their interactions with colleagues, while an electronic survey questionnaire yielded data from 211 level 4 managers. The rationale for selecting this category of managers was that they not only manage staff, but also control a budget, and would find it useful to utilise analytics to aid the decision making process. Qualitative and quantitative data analysis methods were used to analyse the data. Dominant themes that emerged from interviews with eight level 4 managers were: organisational factors and system quality characteristics. Daily log on statistics collected from the electronic survey questionnaire yielded quantitative results on usage of analytics within the organisation. Overall, it was found that managers’ use of analytics is low. Given the importance of analytics for informed decision-making, recommendations are made to increase usage.
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32

Thompson, Stephanie C. "Rational design theory: a decision-based foundation for studying design methods." Diss., Georgia Institute of Technology, 2011. http://hdl.handle.net/1853/39490.

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While design theories provide a foundation for representing and reasoning about design methods, existing design theories do not explicitly include uncertainty considerations or recognize tradeoffs between the design artifact and the design process. These limitations prevent the existing theories from adequately describing and explaining observed or proposed design methods. In this thesis, Rational Design Theory is introduced as a normative theoretical framework for evaluating prescriptive design methods. This new theory is based on a two-level perspective of design decisions in which the interactions between the artifact and the design process decisions are considered. Rational Design Theory consists of normative decision theory applied to design process decisions, and is complemented by a decision-theory-inspired conceptual model of design. The application of decision analysis to design process decisions provides a structured framework for the qualitative and quantitative evaluation of design methods. The qualitative evaluation capabilities are demonstrated in a review of the systematic design method of Pahl and Beitz. The quantitative evaluation capabilities are demonstrated in two example problems. In these two quantitative examples, Value of Information analysis is investigated as a strategy for deciding when to perform an analysis to gather additional information in support of a choice between two design concepts. Both quantitative examples demonstrate that Value of Information achieves very good results when compared to a more comprehensive decision analysis that allows for a sequence of analyses to be performed.
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Simpson, Edwin Daniel. "Combined decision making with multiple agents." Thesis, University of Oxford, 2014. http://ora.ox.ac.uk/objects/uuid:f5c9770b-a1c9-4872-b0dc-1bfa28c11a7f.

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In a wide range of applications, decisions must be made by combining information from multiple agents with varying levels of trust and expertise. For example, citizen science involves large numbers of human volunteers with differing skills, while disaster management requires aggregating information from multiple people and devices to make timely decisions. This thesis introduces efficient and scalable Bayesian inference for decision combination, allowing us to fuse the responses of multiple agents in large, real-world problems and account for the agents’ unreliability in a principled manner. As the behaviour of individual agents can change significantly, for example if agents move in a physical space or learn to perform an analysis task, this work proposes a novel combination method that accounts for these time variations in a fully Bayesian manner using a dynamic generalised linear model. This approach can also be used to augment agents’ responses with continuous feature data, thus permitting decision-making when agents’ responses are in limited supply. Working with information inferred using the proposed Bayesian techniques, an information-theoretic approach is developed for choosing optimal pairs of tasks and agents. This approach is demonstrated by an algorithm that maintains a trustworthy pool of workers and enables efficient learning by selecting informative tasks. The novel methods developed here are compared theoretically and empirically to a range of existing decision combination methods, using both simulated and real data. The results show that the methodology proposed in this thesis improves accuracy and computational efficiency over alternative approaches, and allows for insights to be determined into the behavioural groupings of agents.
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34

Harrison, Michael J. "The enhancement of intra-operative diagnostics and decision-making using computational methods." Thesis, University of Auckland, 2005. http://hdl.handle.net/2292/74.

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The data presented and views expressed in this document are the result of multiple published and unpublished studies over the last 25 years. My over-arching goal in this research was to use modern computing power to create functionally useful diagnoses, in real time, from the monitoring systems used during routine anaesthesia and to present these diagnoses in an ergonomic manner. In addition it was intended to incorporate into the anaesthetic monitor, expert systems that help with the management of uncommon situations. The Australian and New Zealand College guidelines on monitoring during anaesthesia dictate those measurements that should be made during every anaesthetic; from these data evidence can be gathered, integrated, and presented to the clinician. Constraints in this field of research include the inability of the monitors to see, hear or understand the context of operating theatre activities, and computer processing time. Because many studies are involved the methods are detailed in the main text, and are not summarized here. Physiological 'envelopes' have been developed, in which the 'normal' variation in physiological variables, during anaesthesia, are enclosed. They have enabled the creation of intelligent alarm systems that can suggest diagnoses. A retrospective off-line study showed that it was possible to diagnose the onset of malignant hyperpyrexia, using fuzzy logic templates, about 10minutes earlier than the clinician. Some variables may be more important than others in making a diagnosis, and the strength of a diagnosis depends on the amount of supporting evidence, the amount of evidence not against the diagnosis and the amount of missing data. Decision-making (for example to transfuse or not transfuse blood) can also be mathematically modelled so that decision making is more consistent. Finally, investigation of the ways of displaying data indicates that the output can be very explicit. My overall conclusion is that real time decision support systems for the management of clinical dilemmas are possible. They can be instantly and easily accessible and can sit discretely in the background of anaesthetic monitors to be activated at will by the anaesthetist.
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35

Bredell, Marius. "A comparative study of multiple criteria decision making methods for contractor selection." Thesis, Stellenbosch : Stellenbosch University, 2003. http://hdl.handle.net/10019.1/53232.

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Thesis (MBA)--Stellenbosch University, 2003.
ENGLISH ABSTRACT: One of the most difficult and more important decisions taken by a client is the selection of the most appropriate contractor. It requires the assessment of various factors, often conflicting, in order to determine the most appropriate contractor and are therefore classified as a problem that can be resolved by using multiple criteria decision making methods. The act of decision making is never an easy one and requires a sound understanding of the requirement, the alternatives and the model used to assess the alternatives in terms of the requirement in order to instil confidence that the most appropriate alternative is selected. The appropriateness of the methods used in contractor evaluation has a vital impact on the cost of the transaction. The three broad categories, or schools of thought, relating to multiple criteria decision making (MCDM) methods are assessed in terms of their applicability to the contractor selection problem within a quasi-government organisation, namely Armscor. Of the three categories, only the methods of the value measurement category were found to be appropriate within the current legislative framework of the Preferential Procurement Act, which seeks to express the performance of an offer as a unique numerical function. The old contractor selection model of direct point allocation on a qualitative scale is shown to be inappropriate, especially in terms of the additive utility assumption of single dimensional units. The proposed new model makes use of the weighted product model that is not restricted by the additive utility assumption as it results in dimensionless analysis of the criteria. The utility functions associated with the quantitative criteria uses curves which are raised to the power of the confidence variable. The arithmetic mean of these variables represents the group’s confidence level associated with each contractor’s offer in the correctness and/or its ability to maintain the stated level of performance. Furthermore, the analytic hierarchy process is used for the assessment of the qualitative criteria. The new model, although not perfect, is an improvement over the old model with regards to the understanding of the requirement as well as the assessment of contractors’ proposals.
AFRIKAANSE OPSOMMING: Die keuse van ‘n kontrakteur is een van die moeilikste besluite wat ‘n kliënt moet neem, dit is egter ook een van die belangrikste besluite wat geneem word. Ten einde die mees geskikte kontrakteur te kies, moet daar ‘n waarde geheg word aan verskeie faktore, menigmaal teenstrydig, wat kontrakteur seleksie klassifiseer as ‘n probleem wat deur middel van meervoudige-kriteria-besluitnemingsmetodes opgelos kan word. Die handeling van besluitneming is nooit ‘n maklike een en vereis deeglike kennis van die behoefte, die alternatiewe, asook die model wat gebruik word om die alternatiewe in terme van die behoefte te waardeer in orde om vertroue in die gekose alternatief te hê. Vir die doeleindes van hierdie studie is die drie kategorieë van meervoudige-kriteria-besluitnemingsmetodes vergelyk in terme van hul toepaslikheid op die voorafgenoemde probleem binne ‘n Semi-Staatsinstelling, naamlik Krygkor, met die oogmerk om die beste metode te identifiseer. Slegs die metodes vervat in die waarde-meting kategorie is geskik binne die Wet op die Raamwerk vir Voorkeurverkrygingsbeleid wat die evaluasie van ‘n aanbod uitdruk as ‘n unieke numeriese funksie. Uit die studie blyk dit dat die vorige kontrakteur seleksie model van direkte punt allokasie op ‘n kwalitatiewe skaal onvanpas is, veral in terme van die sommerings-nutfunksie aanname van enkel dimensionele eenhede. Die model wat eerder aanbeveel word, maak gebruik van die geweegde-produk-model wat nie beperk word deur die bogenoemde aanname nie, aangesien dit dimensielose analise tot gevolg het. Nutfunksies wat geassosieër word met kwantitatiewe kriteria, word voorgestel deur kurwes wat tot die mag van die vertrouensvlak-veranderlike gehef word. Die rekenkundige gemiddelde van hierdie veranderlike verteenwoordig die groep se vertrouensvlak met betrekking tot elke kontrakteur se akkuraatheid en vermoeë om die gespesifiseerde vlak van werkverrigting te handhaaf. Die kwalitatiewe kriteria word beoordeel deur gebruik te maak van die analitiese hiërargie proses. Die gevolgtrekking wat uiteindelik gemaak word is dat die nuwe model, alhoewel nie foutloos, tog ‘n verbetering is op die vorige model, veral met betrekking tot die insig wat verkry word deur die ontleding van die kontrakteurs se voorstelle in terme van die bepaalde behoefte wat bevredig moet word, ten einde die beste keuse uit te oefen.
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36

Ray, Jessica. "Training for Decision Making in Complex Environments: Instructional Methods and Individual Differences." Doctoral diss., University of Central Florida, 2013. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/5690.

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Increased technology reliance along with today's global fast paced society has produced increasingly complex, dynamic operating environments in disciplines as diverse as the military, healthcare, and transportation. These complex human machine systems often place additional cognitive and metacognitive demands on the operator. Thus, there is a crucial need to develop training tools for all levels of operators in these dynamic systems. The current study was designed to empirically test the effects of four training methods on performance and mental model accuracy in a microworld simulation game. It was hypothesized that process-focused guidance targeting metacognitive level processes as well as combined process and problem focused guidance would result in better performance and mental model accuracy than problem- focused guidance alone or unguided training approaches. Additionally, it was expected that individual differences in prior decision making ability, metacognitive awareness, working memory span, and fluid intelligence would moderate the relationship between the type of instructional guidance and outcomes. Results supported the development of decision-making skills through process-focused instructional guidance, particularly for initially low performing or more novice individuals. Results highlight the importance of individual learner experience prior to training. Similarly, this research aims to expand the literature by providing support for process-focused training as a method to support non-expert decision making skills. While further research needs are outlined, the current research represents an important step forward in both the theoretical literature providing support for instruction designed to support domain general decision making skills in non-experts. Practical implications regarding improved guidance for future instructional and training systems design, personnel selection, operator and system performance evaluation, and safety are also discussed.
Ph.D.
Doctorate
Psychology
Sciences
Psychology; Human Factors Psychology
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37

Dosne, Anne-Gaëlle. "Improved Methods for Pharmacometric Model-Based Decision-Making in Clinical Drug Development." Doctoral thesis, Uppsala universitet, Institutionen för farmaceutisk biovetenskap, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-305697.

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Pharmacometric model-based analysis using nonlinear mixed-effects models (NLMEM) has to date mainly been applied to learning activities in drug development. However, such analyses can also serve as the primary analysis in confirmatory studies, which is expected to bring higher power than traditional analysis methods, among other advantages. Because of the high expertise in designing and interpreting confirmatory studies with other types of analyses and because of a number of unresolved uncertainties regarding the magnitude of potential gains and risks, pharmacometric analyses are traditionally not used as primary analysis in confirmatory trials. The aim of this thesis was to address current hurdles hampering the use of pharmacometric model-based analysis in confirmatory settings by developing strategies to increase model compliance to distributional assumptions regarding the residual error, to improve the quantification of parameter uncertainty and to enable model prespecification. A dynamic transform-both-sides approach capable of handling skewed and/or heteroscedastic residuals and a t-distribution approach allowing for symmetric heavy tails were developed and proved relevant tools to increase model compliance to distributional assumptions regarding the residual error. A diagnostic capable of assessing the appropriateness of parameter uncertainty distributions was developed, showing that currently used uncertainty methods such as bootstrap have limitations for NLMEM. A method based on sampling importance resampling (SIR) was thus proposed, which could provide parameter uncertainty in many situations where other methods fail such as with small datasets, highly nonlinear models or meta-analysis. SIR was successfully applied to predict the uncertainty in human plasma concentrations for the antibiotic colistin and its prodrug colistin methanesulfonate based on an interspecies whole-body physiologically based pharmacokinetic model. Lastly, strategies based on model-averaging were proposed to enable full model prespecification and proved to be valid alternatives to standard methodologies for studies assessing the QT prolongation potential of a drug and for phase III trials in rheumatoid arthritis. In conclusion, improved methods for handling residual error, parameter uncertainty and model uncertainty in NLMEM were successfully developed. As confirmatory trials are among the most demanding in terms of patient-participation, cost and time in drug development, allowing (some of) these trials to be analyzed with pharmacometric model-based methods will help improve the safety and efficiency of drug development.
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38

Burton, Rita Maria. "Decision-making in older women with breast cancer : a mixed methods study." Thesis, Sheffield Hallam University, 2017. http://shura.shu.ac.uk/18143/.

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Background and aims: In the United Kingdom one third of all breast cancers are diagnosed in women aged 70 or over. Older women with breast cancer are less likely to be offered or receive standard treatment. Aim: The overarching aim of this study was to establish the information needs and decision-making preferences of older women diagnosed with primary, operable, oestrogen receptor positive breast cancer and faced with a choice of surgery or primary endocrine therapy (PET). Research design and methods: This exploratory, sequential mixed methods study comprised a critical review of the literature, qualitative interviews and a quantitative questionnaire. The findings were interpreted and integrated in line with the mixed method ethos. Key Findings: The findings are underpinned by varied and complex internal and external influences. It is accepted that with increasing age cognitive functioning is compromised and poor health literacy is common. Although, the views of HCPs influenced treatment decisions, contrary to previously reported studies older women in this study wanted active involvement in the decision-making process and demonstrated confidence when making treatment choices. In terms of the content and format of information, unsurprisingly women preferred tailored information delivered face to face by the specialist HCP. In terms of written information women wanted brevity and simplicity. Visual displays of numeric data were unpopular and were found to be confusing for most women. Conclusions and recommendations: Information and decision support needs varied among this group of women. Understanding how older women define 'involvement in treatment decision-making' would enhance the development of appropriate decision support. Further work is required in the development of data collection tools, particularly questionnaires, appropriate for an older, frail population.
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39

Ryu, Young Sam. "Development of Usability Questionnaires for Electronic Mobile Products and Decision Making Methods." Diss., Virginia Tech, 2005. http://hdl.handle.net/10919/28746.

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As the growth of rapid prototyping techniques shortens the development life cycle of software and electronic products, usability inquiry methods can play a more significant role during the development life cycle, diagnosing usability problems and providing metrics for making comparative decisions. A need has been realized for questionnaires tailored to the evaluation of electronic mobile products, wherein usability is dependent on both hardware and software as well as the emotional appeal and aesthetic integrity of the design. This research followed a systematic approach to develop a new questionnaire tailored to measure the usability of electronic mobile products. The Mobile Phone Usability Questionnaire (MPUQ) developed throughout this series of studies evaluates the usability of mobile phones for the purpose of making decisions among competing variations in the end-user market, alternatives of prototypes during the development process, and evolving versions during an iterative design process. In addition, the questionnaire can serve as a tool for identifying diagnostic information to improve specific usability dimensions and related interface elements. Employing the refined MPUQ, decision making models were developed using Analytic Hierarchy Process (AHP) and linear regression analysis. Next, a new group of representative mobile users was employed to develop a hierarchical model representing the usability dimensions incorporated in the questionnaire and to assign priorities to each node in the hierarchy. Employing the AHP and regression models, important usability dimensions and questionnaire items for mobile products were identified. Finally, a case study of comparative usability evaluations was performed to validate the MPUQ and models. A computerized support tool was developed to perform redundancy and relevancy analyses for the selection of appropriate questionnaire items. The weighted geometric mean was used to combine multiple numbers of matrices from pairwise comparison based on decision makers' consistency ratio values for AHP. The AHP and regression models provided important usability dimensions so that mobile device usability practitioners can simply focus on the interface elements related to the decisive usability dimensions in order to improve the usability of mobile products. The AHP model could predict the users' decision based on a descriptive model of purchasing the best product slightly but not significantly better than other evaluation methods. Except for memorability, the MPUQ embraced the dimensions included in the other well-known usability definitions and almost all criteria covered by the existing usability questionnaires. In addition, MPUQ incorporated new criteria, such as pleasurability and specific tasks performance.
Ph. D.
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40

Shan, Yixing. "Decision making study : methods and applications of evidential reasoning and judgment analysis." Thesis, Loughborough University, 2015. https://dspace.lboro.ac.uk/2134/17330.

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Decision making study has been the multi-disciplinary research involving operations researchers, management scientists, statisticians, mathematical psychologists and economists as well as others. This study aims to investigate the theory and methodology of decision making research and apply them to different contexts in real cases. The study has reviewed the literature of Multiple Criteria Decision Making (MCDM), Evidential Reasoning (ER) approach, Naturalistic Decision Making (NDM) movement, Social Judgment Theory (SJT), and Adaptive Toolbox (AT) program. On the basis of these literatures, two methods, Evidence-based Trade-Off (EBTO) and Judgment Analysis with Heuristic Modelling (JA-HM), have been proposed and developed to accomplish decision making problems under different conditions. In the EBTO method, we propose a novel framework to aid people s decision making under uncertainty and imprecise goal. Under the framework, the imprecise goal is objectively modelled through an analytical structure, and is independent of the task requirement; the task requirement is specified by the trade-off strategy among criteria of the analytical structure through an importance weighting process, and is subject to the requirement change of a particular decision making task; the evidence available, that could contribute to the evaluation of general performance of the decision alternatives, are formulated with belief structures which are capable of capturing various format of uncertainties that arise from the absence of data, incomplete information and subjective judgments. The EBTO method was further applied in a case study of Soldier system decision making. The application has demonstrated that EBTO, as a tool, is able to provide a holistic analysis regarding the requirements of Soldier missions, the physical conditions of Soldiers, and the capability of their equipment and weapon systems, which is critical in domain. By drawing the cross-disciplinary literature from NDM and AT, the JA-HM extended the traditional Judgment Analysis (JA) method, through a number of novel methodological procedures, to account for the unique features of decision making tasks under extreme time pressure and dynamic shifting situations. These novel methodological procedures include, the notion of decision point to deconstruct the dynamic shifting situations in a way that decision problem could be identified and formulated; the classification of routine and non-routine problems, and associated data alignment process to enable meaningful decision data analysis across different decision makers (DMs); the notion of composite cue to account for the DMs iterative process of information perception and comprehension in dynamic task environment; the application of computational models of heuristics to account for the time constraints and process dynamics of DMs decision making process; and the application of cross-validation process to enable the methodological principle of competitive testing of decision models. The JA-HM was further applied in a case study of fire emergency decision making. The application has been the first behavioural test of the validity of the computational models of heuristics, in predicting the DMs decision making during fire emergency response. It has also been the first behavioural test of the validity of the non-compensatory heuristics in predicting the DMs decisions on ranking task. The findings identified extend the literature of AT and NDM, and have implications for the fire emergency decision making.
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41

Zhou, Sida. "The Development and Evaluation of Aggregation Methods for Group Pairwise Comparison Judgments." PDXScholar, 1996. https://pdxscholar.library.pdx.edu/open_access_etds/1222.

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The basic problem of decision making is to choose the best alternative from a set of competing alternatives that are evaluated under conflicting criteria. In general, the process is to evaluate decision elements by quantifying the subjective judgments. The Analytic Hierarchy Process (AHP) provides us with a comprehensive framework for solving such problems. As pointed out by Saaty, AHP "enables us to cope with the intuitive, the rational, and the irrational, all at the same time, when we make multicriteria and multiactor decisions". Furthermore, in most organizations decisions are made collectively, regardless of whether the organization is public or private. It is sometimes difficult to achieve consensus among group members, or for all members of a group to meet. The purpose of this dissertation was two-fold: First, we developed a new aggregation method - Minimum Distance Method (MDM) - to support group decision process and to help the decision makers achieve consensus under the framework of AHP. Second, we evaluated the performance of aggregation methods by using accuracy and group disagreement criteria. The evaluations were performed through simulation and empirical tests. MDM • employs the general distance concept, which is very appealing to the compromise nature of a group decision making. • preserves all of the characteristics of the functional equations approach proposed by Aczel and Saaty. • is based on a goal programming model, which is easy to solve by using a commercial software such as LINDO. • provides the weighted membership capability for participants. • allows for sensitivity analysis to investigate the effect of importance levels of decision makers in the group. The conclusions include the following: • Simulation and empirical tests show that the two most important factors in the aggregation of pairwise comparison judgments are the probability distribution of error terms and the aggregation method. • Selection of the appropriate aggregation method can result in significant improvements in decision quality. • The MDM outperforms the other aggregation methods when the pairwise comparison judgments have large variances. • Some of the prioritization methods, such as EV[AA'], EV[A'A], arithmetic and geometric mean of EV[AA'] and EV[A'A], can be dropped from consideration due to their poor performance
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42

Chinyamakobvu, Mutsa Carole. "Eliciting and combining expert opinion : an overview and comparison of methods." Thesis, Rhodes University, 2015. http://hdl.handle.net/10962/d1017827.

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Decision makers have long relied on experts to inform their decision making. Expert judgment analysis is a way to elicit and combine the opinions of a group of experts to facilitate decision making. The use of expert judgment is most appropriate when there is a lack of data for obtaining reasonable statistical results. The experts are asked for advice by one or more decision makers who face a specific real decision problem. The decision makers are outside the group of experts and are jointly responsible and accountable for the decision and committed to finding solutions that everyone can live with. The emphasis is on the decision makers learning from the experts. The focus of this thesis is an overview and comparison of the various elicitation and combination methods available. These include the traditional committee method, the Delphi method, the paired comparisons method, the negative exponential model, Cooke’s classical model, the histogram technique, using the Dirichlet distribution in the case of a set of uncertain proportions which must sum to one, and the employment of overfitting. The supra Bayes approach, the determination of weights for the experts, and combining the opinions of experts where each opinion is associated with a confidence level that represents the expert’s conviction of his own judgment are also considered.
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43

Wallenius, Hannele. "Implementing interactive multiple criteria decision methods in public policy /." Jyväskylä : University of Jyväskylä, 1991. http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&doc_number=005963002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA.

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44

Andersen, Frans, and David Fagersand. "Forecasting commodities : - A study of methods, interests and preception." Thesis, Uppsala universitet, Företagsekonomiska institutionen, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-230411.

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This study aims to investigate reasons for variation in accuracy between different forecast methods by studying the choice of methods, learning processes, biases and opinions within the firms using them; enabling us to provide recommendations of how to improve accuracy within each forecast method. Eleven Swedish and international companies that are regularly forecasting commodity price-levels have been interviewed. Since there is a cultural aspect to the development of forecast methods; the authors have chosen to conduct a qualitative study, using a semi-structured interview technique that enables us to illustrate company-specific determinants. The results show that choice of methods, learning processes, biases and opinions all have potentially substantial implications on the accuracy achieved. The phenomena’s individual implication on accuracy varies amongst method-group.
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45

Vavrek, R. "Use of selected methods multi-criteria decision." Thesis, Сумський державний університет, 2014. http://essuir.sumdu.edu.ua/handle/123456789/34561.

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The purpose of multi-criteria decision models is to help decision maker to evaluate each alternative and to rank them in descending order of performance. This study analyses the base of concept of Multiple Attribute Decision Making for using in different areas. The aim of this paper is to describe the concept of multiple attribute decision making. Achieving this purpose, TOPSIS technique is used as decision making tools. When you are citing the document, use the following link http://essuir.sumdu.edu.ua/handle/123456789/34561
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46

ATHEY, SUSAN. "A MENTOR SYSTEM INCORPORATING EXPERTISE TO GUIDE AND TEACH STATISTICAL DECISION-MAKING." Diss., The University of Arizona, 1987. http://hdl.handle.net/10150/184011.

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The statistical mentor system incorporates a knowledge base into an educational tool for novices in statistical decision making to use in choosing a statistical technique. The novices are students in a business school curriculum who are expected to learn the basic statistical processes in business applications. The purpose of the system is to stimulate learning of the data analysis process on the part of the novice, usually a difficult task. The system acts as a consultant to the novice and approaches the task using a top-down problem solving strategy rather than the traditional bottom-up strategy used by novices. The heart of the system is the rule base for differentiating between statistics. These rules were built by gathering expertise from two experts in statistical analysis. The rules are based on five questions which the data can answer, as well as the type of data, the number of variables, and any dependent/independent relationships which exist between the variables. The knowledge base consists of five rule sets and can be represented either by condition/conclusion rules or by a set of multi-dimensional tables. Twenty-nine statistics and the rules for choosing them are in the rules sets. The knowledge base was used to define the logic incorporated in the consultant system in order to aid the user in selecting a correct technique. A dialogue mode is employed in the consultant to determine which conditions are true for the problem and data set. The rule sets are then checked to find the conclusion satisfying the conditions. The computer mentor was tested against the usual textbook mentor method (search through a textbook until one finds a statistic that looks promising) with two different groups of subjects, 25 undergraduates and 19 doctoral students. The results were that the computer-assisted students in both samples correctly solved a larger proportion of problems and had a higher average number of problems correct than did the textbook assisted groups.
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47

Johnson, Nicolas R. "Building Energy Model Calibration for Retrofit Decision Making." PDXScholar, 2017. https://pdxscholar.library.pdx.edu/open_access_etds/3507.

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Accommodating the continued increase in energy demand in the face of global climate change has been a worldwide concern. With buildings in the US consuming nearly 40% of national energy, a concerted effort must be given to reduce building energy consumption. As new buildings continue to improve their efficiency through more restrictive energy codes, the other 76.9 billion square feet of current building stock falls further behind. The rate at which current buildings are being retrofit is not enough and better tools are needed to access the benefits of retrofits and the uncertainties associated with them. This study proposes a stochastic method of building energy model calibration coupled with a monthly normative building simulation addressed in ISO 13890. This approach takes advantage of the great efficiency of Latin Hypercube Sampling and the lightweight normative building simulation method, to deliver a set of calibrated solutions to assess the effectiveness of energy conservation measure, making uncertainty a part of the modeling process. A case study on a mixed-use university building is conducted to show the strength and performance of this simple method. Limitations and future concerns are also addressed.
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48

Payan, Alexia Paule Marie-Renee. "Enabling methods for the design and optimization of detection architectures." Diss., Georgia Institute of Technology, 2013. http://hdl.handle.net/1853/47688.

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The surveillance of geographic borders and critical infrastructures using limited sensor capability has always been a challenging task in many homeland security applications. While geographic borders may be very long and may go through isolated areas, critical assets may be large and numerous and may be located in highly populated areas. As a result, it is virtually impossible to secure each and every mile of border around the country, and each and every critical infrastructure inside the country. Most often, a compromise must be made between the percentage of border or critical asset covered by surveillance systems and the induced cost. Although threats to homeland security can be conceived to take place in many forms, those regarding illegal penetration of the air, land, and maritime domains under the cover of day-to-day activities have been identified to be of particular interest. For instance, the proliferation of drug smuggling, illegal immigration, international organized crime, resource exploitation, and more recently, modern piracy, require the strengthening of land border and maritime awareness and increasingly complex and challenging national security environments. The complexity and challenges associated to the above mission and to the protection of the homeland may explain why a methodology enabling the design and optimization of distributed detection systems architectures, able to provide accurate scanning of the air, land, and maritime domains, in a specific geographic and climatic environment, is a capital concern for the defense and protection community. This thesis proposes a methodology aimed at addressing the aforementioned gaps and challenges. The methodology particularly reformulates the problem in clear terms so as to facilitate the subsequent modeling and simulation of potential operational scenarios. The needs and challenges involved in the proposed study are investigated and a detailed description of a multidisciplinary strategy for the design and optimization of detection architectures in terms of detection performance and cost is provided. This implies the creation of a framework for the modeling and simulation of notional scenarios, as well as the development of improved methods for accurate optimization of detection architectures. More precisely, the present thesis describes a new approach to determining detection architectures able to provide effective coverage of a given geographical environment at a minimum cost, by optimizing the appropriate number, types, and locations of surveillance and detection systems. The objective of the optimization is twofold. First, given the topography of the terrain under study, several promising locations are determined for each sensor system based on the percentage of terrain it is covering. Second, architectures of sensor systems able to effectively cover large percentages of the terrain at minimal costs are determined by optimizing the number, types and locations of each detection system in the architecture. To do so, a modified Genetic Algorithm and a modified Particle Swarm Optimization are investigated and their ability to provide consistent results is compared. Ultimately, the modified Particle Swarm Optimization algorithm is used to obtain a Pareto frontier of detection architectures able to satisfy varying customer preferences on coverage performance and related cost.
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49

Riabacke, Ari. "Development of Elicitation Methods for Managerial Decision Support." Doctoral thesis, Sundsvall : Mittuniversitetet, 2007. http://urn.kb.se/resolve?urn=urn:nbn:se:miun:diva-40.

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50

Gowen, Jeffrey Bryan. "Methods Used in Public Policy Decision Making by County Managers in North Carolina." ScholarWorks, 2015. https://scholarworks.waldenu.edu/dissertations/356.

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Researchers have examined ways in which policy makers develop their decisions. The literature has not explored, however, the methodologies used by county managers to arrive at decisions, or whether they consider the medium- and long-term policy implications, or second and third order effects, of those decisions. The purpose of this study was to identify the methodologies and decision-making processes used by county managers in North Carolina. The theoretical framework was Lindblom's theory of incrementalism in decision making. Data for this phenomenological study were collected through semi-structured interviews with 10 purposefully selected county managers, and were coded and categorized to identify themes and patterns. Results indicated that county managers tended to rely on multiple methodologies, rather than one consistent methodology, when deciding public policy issues, and that they overwhelmingly considered the second and third order effects of their decisions on public policy outcomes. The implications for positive social change include informing country managers and the public about policy decisions and their effects on the long-term well-being of their local community.
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