Relevant bibliographies by topics / Evaluation model

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Evaluation model'

Author: Grafiati
Published: 4 June 2021
Last updated: 25 September 2024

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Journal articles on the topic "Evaluation model"

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NICA, Panaite, and Silviu Mihail TITA. "Efficiency – Model for Scientific Research Evaluation." Revista Romaneasca pentru Educatie Multidimensionala 5, no. 1 (June 30, 2013): 141–59. http://dx.doi.org/10.18662/rrem/2013.0501.10.

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Lahajnar, Sebastian, and Alenka Rožanec. "Initial Coin Offering (ICO) evaluation model." Investment Management and Financial Innovations 15, no. 4 (November 19, 2018): 169–82. http://dx.doi.org/10.21511/imfi.15(4).2018.14.

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High-tech companies operating in the field of blockchain technology use the Initial Coin Offering (ICO) to raise start-up capital. It is a fairly new, non-standardized and poorly regulated way of collecting start-up funding that can bring high yields to investors in the short term, but investors also have to be ready to take on high risks. The purpose of this article is to define a decision model for the evaluation of ICO projects, which provides a systematic, transparent, methodological approach to making decisions on investing in them. For that purpose, the authors analyzed a number of factors, which directly or indirectly influence the successful implementation of ICO projects, and the researchers extracted the most important among them (model parameters). In order to build the decision model, used a qualitative method for the hierarchical multi-parameter evaluation of DEX, which using symbolic parameters and combining functions in the form of if-then rules ensures the most freely and flexible combining assessment parameters into a uniform model. In the article, the use of proposed decision model was tested in practice on multiple ICO processes. The article details the decision-making process in the case of CargoX, and also summarizes the results of the evaluation of ICOs Tokens.net, BitClave, Neuromation and WePower.
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Masood Butt, Saad, Shahid Masood Butt, Azura Onn, Nadra Tabassam, and Mazlina Abdul Majid. "Usability Evaluation Techniques for Agile Software Model." Journal of Software 10, no. 1 (January 2015): 32–41. http://dx.doi.org/10.17706/jsw.10.1.32-41.

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Munro, Barbara Hazard. "Evaluation Model." Clinical Nurse Specialist 9, no. 3 (May 1995): 144. http://dx.doi.org/10.1097/00002800-199505000-00007.

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Sparks, Elizabeth, Michelle Molina, Natalie Shepp, and Fiona Davey. "The Evaluation Skill-a-Thon: Evaluation Model for Meaningful Youth Engagement." Journal of Youth Development 16, no. 1 (March 30, 2021): 100–125. http://dx.doi.org/10.5195/jyd.2021.968.

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Active engagement of youth participants in the evaluation process is an increasingly sought out method, but the field can still benefit from new methods that ease youth participatory evaluation implementation. Meaningful youth engagement in the evaluation process is particularly advantageous under the 4-H thriving model because of its potential to contribute to positive youth development, foster relationship building, enhance evaluation capacity, and improve program quality through improved evaluations. This program sought to facilitate actively engaging youth in the evaluation process by breaking it up into clear and manageable steps including evaluation design, data collection, data interpretation and analysis, reporting results, and outlining programmatic change. To achieve this aim, program staff designed the Evaluation Skill-a-Thon, a set of self-paced, experiential evaluation activities at various stations through which youth participants rotate. Actively involving youth participants in the evaluation process using the Skill-a-Thon model resulted in youth being able to identify and design programmatic changes, increased participation and response rates in other evaluations, and several youth participants’ gaining an interest in evaluation and working to design evaluations in later years. The Evaluation Skill-a-Thon holds promise for actively engaging youth participants in the entire evaluation process, easy implementation, and increasing evaluation capacity.
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Lim, Hee-Jeong, Young-Hee Lee, and Hyo-Jung Kwon. "Evaluation of Community Land Model version 3.5-Dynamic Global Vegetation Model over Deciduous Forest in Gwangneung, Korea." Korean Journal of Agricultural and Forest Meteorology 12, no. 2 (June 30, 2010): 95–106. http://dx.doi.org/10.5532/kjafm.2010.12.2.095.

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Turgut, Mehmet, and Alp Ustundag. "A Hybrid Risk Evaluation Model for Automotive Production." International Journal of Machine Learning and Computing 4, no. 5 (2014): 458–62. http://dx.doi.org/10.7763/ijmlc.2014.v4.454.

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Tvrdoň, J. "Some model approaches of natural resources efficiency evaluation." Agricultural Economics (Zemědělská ekonomika) 51, No. 2 (February 20, 2012): 47–50. http://dx.doi.org/10.17221/5075-agricecon.

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The article deals with problems of sustainable development of agriculture from the viewpoint of efficient use of environmental resources. Environmental resources are factors of creation both usual economic goods and stabilization of environment. Analysis proved that classical indicators of economic performance are necessary to be modified by the ecological threshold of economic activities. However its level is not fixed and follows factors introduced in the paper which arose in frame of solution of the Institutional Research Intention MSM 411100013.
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Kozyk, V., O. Mrykhina, and T. Mirkunova. "Conceptual Model for Economic Evaluation of Innovative Technologies." Economics, Entrepreneurship, Management 4, no. 2 (2017): 45–58. http://dx.doi.org/10.23939/eem2017.02.045.

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Icke, J., K. J. van Heeringen, S. Groot, and M. Ouboter. "Model Evaluation Tool experiences for the Amstel River." River Systems 17, no. 1-2 (July 28, 2006): 97–113. http://dx.doi.org/10.1127/lr/17/2006/97.

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Dissertations / Theses on the topic "Evaluation model"

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Tudevdagva, Uranchimeg. "Structure Oriented Evaluation Model for E-Learning." Doctoral thesis, Universitätsbibliothek Chemnitz, 2014. http://nbn-resolving.de/urn:nbn:de:bsz:ch1-qucosa-146901.

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Volume 14 of publication series EINGEBETTETE, SELBSTORGANISIERENDE SYSTEME is devoted to the structure oriented evaluation of e-learning. For future knowledge society, beside creation of intelligent technologies, adapted methods of knowledge transfer are required. In this context e-learning becomes a key technology for development of any education system. E-learning is a complex process into which many different groups with specific tasks and roles are included. The dynamics of an e-learning process requires adjusted quality management. For that corresponding evaluation methods are needed. In the present work, Dr.Tudevdagva develops a new evaluation approach for e-learning. The advantage of her method is that in contrast to linear evaluation methods no weight factors are needed and the logical goal structure of an elearning process can be involved into evaluation. Based on general measure theory structure oriented score calculation rules are derived. The so obtained score function satisfies the same calculation rules as they are known from normalised measures. In statistical generalisation, these rules allow the structure oriented calculation of empirical evaluation scores based on checklist data. By these scores the quality can be described by which an e-learning has reached its total goal. Moreover, a consistent evaluation of embedded partial processes of an e-learning becomes possibly. The presented score calculation rules are part of a eight step evaluation model which is illustrated by pilot samples. U. Tudevdagva’s structure oriented evaluation model (SURE model) is by its embedding into the general measure theory quite universal applicable. In similar manner, an evaluation of efficiency of administration or organisation processes becomes possible.
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Nordholm, Johan. "Model-Based Testing: An Evaluation." Thesis, Karlstad University, Faculty of Economic Sciences, Communication and IT, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:kau:diva-5188.

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Testing is a critical activity in the software development process in order to obtain systems of high quality. Tieto typically develops complex systems, which are currently tested through a large number of manually designed test cases. Recent development within software testing has resulted in methods and tools that can automate the test case design, the generation of test code and the test result evaluation based on a model of the system under test. This testing approach is called model-based testing (MBT).

This thesis is a feasibility study of the model-based testing concept and has been performed at the Tieto office in Karlstad. The feasibility study included the use and evaluation of the model-based testing tool Qtronic, developed by Conformiq, which automatically designs test cases given a model of the system under test as input. The experiments for the feasibility study were based on the incremental development of a test object, which was the client protocol module of a simplified model for an ATM (Automated Teller Machine) client-server system. The experiments were evaluated both individually and by comparison with the previous experiment since they were based on incremental development. For each experiment the different tasks in the process of testing using Qtronic were analyzed to document the experience gained as well as to identify strengths and weaknesses.

The project has shown the promise inherent in using a model-based testing approach. The application of model-based testing and the project results indicate that the approach should be further evaluated since experience will be crucial if the approach is to be adopted within Tieto’s organization.

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Klose, Daniel Peter. "Protein model construction and evaluation." Thesis, University College London (University of London), 2008. http://discovery.ucl.ac.uk/1444214/.

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The prediction of protein secondary and tertiary structure is becoming increasingly important as the number of sequences available to the biological community far exceeds the number of unique native structures. The following chapters describe the conception, construction, evaluation and application of a series of algorithms for the prediction and evaluation of two and three-dimensional protein structure. In chapter 1 a brief overview of protein structure and the resources required to predict protein features is given. Chapter 2 describes the investigation of sequence identity and alignments on the prediction of two-dimensional protein structure in the form of long and short range protein contacts a feature which is known to correlate with solvent accessibility. It also describes the identification of a feature which is referred to as the 'Empty Quarter' which forms the basis of an evaluation function described in Chapter 3 and developed in Chapter 4. Chapter 3 introduces the Dynamic Domain Threading method used during round six of the CASP exercise. Phobic, a protein evaluation function based on predicted solvent accessibility is described in Chapter 4. The de novo prediction of a/p proteins is described in Chapter 5, the method introduces a new approach to the old problem of combinatorial modelling and breaks the size limit previously imposed on de novo prediction. The final experimental chapter describes the prediction of solvent accessibility and secondary structure using a novel combination of the fuzzy k-nearest neighbour and support vector machine. Chapter 7 closes this piece of work with a review of the field and suggests potential improvements to the way work is conducted.
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Sharma, Nishchay. "Knock Model Evaluation – Gas Engine." Thesis, KTH, Maskinkonstruktion (Avd.), 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-237133.

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Knocking is a type of abnormal combustion which depends on several physical factors and results in high frequency pressure oscillations inside the combustion chamber of a spark-ignited internal combustion engine (ICE). These oscillations can damage the engine and hamper its efficiency, which is why it is important for automakers to understand the knocking behavior so that it can be avoided during engine operation. Due to the catastrophic outcomes of knocking a lot of research has been done in the past on prediction of its occurrence. There can be several causes of knocking but when it occurs due to auto-ignition of fuel in the end-gas it’s called spark-knock. There are various mathematical models that predict the phenomenon of spark-knock. In this thesis, several of the previously published knock prediction models for heavy-duty natural-gas engine are studied and analyzed. The main objective of this project is to assess the accuracy of different types of knock prediction models.Amongst all the types of knock prediction models emphasize has been given to empirical correlation models, particularly to the ones which are based on chemical kinetics pertaining to the combustion process of methane. These are the models that claim to predict ignition delay time based on concentration of air and fuel in the unburned zone of the cylinder. The models are assessed based on the knocking behavior they represent across the engine operation range. Results pertaining to the knock prediction models are evaluated in a 1D engine simulation model using AVL BOOST. The BOOST performance prediction model is calibrated against experimentally measured engine test-cell data and the same data is used to assess the knock prediction models.The knock prediction model whose results correlate with experimental observations is analyzed further while other models are discarded. Using the validated model, variation in knock occurrence is evaluated with change in the combustion phasing. Two of the parameter that are used to define the combustion phasing are spark-advance and combustion duration. It was found that when the brake mean effective pressure is kept constant the knock prediction parameter increases linearly with increase in spark advance and decreases linearly with increase in combustion duration. The variation of knock prediction parameter with spark advance showed increasing gradient with increase in engine torque.
Knack i en förbränningsmotor är en typ av onormal förbränning. Det är ett komplicerat fenomen som beror på flera fysiska faktorer och resulterar i högfrekventa tryckoscillationer inuti förbränningskammaren. Dessa oscillationer kan skada motorn och fenomenet hämmar motorns effektivitet. Knack kan uppstå på två sätt i en Otto-motor och detta examensarbete kommer att handla om självantändning. Självantändning, i detta fall, är när ändgasen börjar brinna utan att ha blivit påverkad av flamfronten eller gnistan från tändstiftet. Det finns flera olika matematiska modeller som i olika grader kan prediktera knackfenomenet. I detta examensarbete studeras några av de tidigare publicerade prediktionsmodellerna för knack i Otto-förbränning och modelleras för analys. Huvudsyftet med detta projekt är således att bedöma noggrannheten hos olika typer av knackmodeller. Extra fokus har lagts på empiriska korrelationsmodeller, särskilt till de som är baserade på kemisk kinetik avseende förbränningsprocessen av metan. Dessa modeller förutsäger den tid det tar för ändgasen att självantända, baserat på dess koncentration av luft och bränsle. Knackmodellerna bedöms sedan utifrån det beteende som de förutsäger över motorns driftområde och dess överensstämmelse med kända motorkalibreringsstrategier. Resultatet av knackpredikteringen för de olika knackmodellerna utvärderas och valideras i en motorsimuleringsmodell i mjukvaran AVL BOOST. BOOST-modellen kalibreras mot experimentellt uppmätta motortestdata. Baserat på resultaten från de valda knockmodellerna så blev den modell som bäst korrelerar med kända motorkalibreringsstrategier analyserad djupare. Den utvalda modellen var en ECM modell och den utvärderas ytterligare med avseende på variation i predikterad knack-parameter. Detta görs genom att modifiera två förbränningsparametrar: tändvinkel och förbränningsduration. Det visade sig att modellerna predikterade en linjär ökning då tändningen tidigareläggs och ett linjärt minskande vid längre förbränningsduration, vilket är i enlighet med motortestdata. Vidare visade det sig att variationer i tändvinkel resulterade i en högre gradient i knackpredikteringen vid högre motorbelastningar och korresponderande minskning vid lägre belastning.
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Miroshnychenko, Dmytro. "Mechanical behaviour of PVC : model evaluation." Thesis, Loughborough University, 2002. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.250881.

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Al-Dawood, Abdullah Saad. "Transportation and economic development evaluation model." Diss., Virginia Tech, 1990. http://hdl.handle.net/10919/39905.

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The system dynamics methodology is used to develop a computer simulation model to determine whether to add lanes to a congested highway or build a new, more direct, facility. Fundamental to this evaluation is the incorporation of non-user measures of effectiveness to go with the traditional highway user measures of effectiveness, such as the Benefit-Cost Ratio. In the system dynamics methodology three alternative forms of the model of a system are used: verbal, visual, and mathematical. The verbal description is diagrammatic and shows cause-and-effect relationships between many variables in a simple, concise manner. The visual model or "causal diagram" is translated into a mathematical model and system equations. The model is comprised of four sectors: 1. population sector 2. economic sector 3. university sector 4. transportation sector The model applies to the area of Blacksburg, Christiansburg and Roanoke (city and county). with special treatment to Virginia Tech through the university model. The simulation results of the non-user benefits along with user benefits is used to evaluate the alternatives in the Blacksburg-Christiansburg-Roanoke corridor.
Ph. D.
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Aldrete, Sánchez Rafael Manuel. "Feasibility evaluation model for toll highways /." Digital version accessible at:, 1998. http://wwwlib.umi.com/cr/utexas/main.

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Clark, Thomas K. "Logging Subsystem Performance: Model and Evaluation." PDXScholar, 1994. https://pdxscholar.library.pdx.edu/open_access_etds/4724.

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Transaction logging is an integral part of ensuring proper transformation of data from one state to another in modern data management. Because of this, the throughput of the logging subsystem can be critical to the throughput of an application. The purpose of this research is to break the log bottleneck at minimum cost. We first present a model for evaluating a logging subsystem, where a logging subsystem is made up of a log device, a log backup device, and the interconnect algorithm between the two, which we term the log backup method. Included in the logging model is a set of criteria for evaluating a logging subsystem and a system for weighting the criteria in order to facilitate comparisons of two logging subsystem configurations to determine the better of the two. We then present an evaluation of each of the pieces of the logging subsystem in order to increase the bandwidth of both the log device and log backup device, while selecting the best log backup method, at minimum cost. We show that the use of striping and RAID is the best alternative for increasing log device bandwidth. Along with our discussion of RAID, we introduce a new RAID algorithm that is designed to overcome the performance problems of small writes in a RAID log. In order to increase the effective bandwidth of the log backup device, we suggest the use of inexpensive magnetic tape drives and striping in the log backup device, where the bandwidth of the log backup device is increased to the point that it matches the bandwidth of the log device. For the log backup interconnect algorithm, we present the novel approach of backing up the log synchronously, where the log backup device is essentially a mirror of the log device, as well as evaluating other log backup interconnect algorithms. Finally, we present a discussion of a prototype implementation of some of the ideas in the thesis. The prototype was implemented in a commercial database system, using a beta version of INFORMIX-OnLine Dynamic Server™ version 6.0.
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Sirikijpanichkul, Ackchai. "An agent-based location evaluation model." Thesis, Queensland University of Technology, 2008. https://eprints.qut.edu.au/20672/1/Ackchai_Sirikijpanichkul_Thesis.pdf.

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Truck transportation is considered as a favourable mode by shippers to carry freight at most ranges of distance as it has more flexibility in fleet size, capacity, scheduling, routing, and access. Although truck is considered as the popular mode for freight transportation, road-rail intermodal freight transportation becomes an attractive alternative to road only mode since the latter has no longer assured a reliable service due to traffic congestion problem. It also raises public concern in environmental and road safety impacts. Intermodal freight transportation is defined as a system that carries freight from origin to destination using two or more transportation modes where transfers between modes occur at an intermodal freight terminal. Success of the terminal depends on four major factors, namely: location, efficiency, financial sustainability, and rail level of service. Among these, the location is one of the most crucial success factors and needs to be considered carefully as it has direct and indirect impacts on a number of stakeholders including terminal users, terminal operators, transport network infrastructure providers, and community. Limitations of previous terminal location evaluation models in representing individual preference and behaviour as well as accommodating negotiation and communication between the players bring in an opportunity to develop a new model which is more flexible and capable of providing a solution that is not necessary to be optimal, but acceptable for every player without requiring explicit trade-offs. This thesis is aimed at demonstrating the feasibility of applying an agent-based approach to the evaluation of intermodal freight terminal location and investigating terminal effectiveness against stakeholder equity and some important aspects arising from the different stakeholders’ viewpoints. Agent technologies were introduced to model the stakeholders as individual agents. The agent concept was adopted to develop a decentralised location evaluation system that is able to balance the terminal effectiveness with the stakeholder equity. The proposed agent-based location evaluation model was modelled as a hierarchical control system that comprises three decision levels: local level, stakeholder level and policy level. Policy level is the highest decision level, which is represented by a policy maker. Apart from the policy level, the rest can be viewed as operational decision levels. Local level is the lowest control level. At this level, each stakeholder was classified into stakeholder groups based on their characteristics and interest. The terminal scenarios were then evaluated based on benefit maximisation criteria. Stakeholder control is the higher control level than the local level. It represents the control level where negotiations and decisions between groups of people (stakeholders) with different point of views are made. At this level, negotiation process was used to determine terminal location based on preference and equity of stakeholders. The determined terminal site was then used in the evaluation against constraints to ensure that all agents are satisfied. The terminal location decision for South East Queensland (SEQ) was applied as a case study of this thesis. The SEQ strategic freight transport model was developed, calibrated, and validated to assist in providing inputs for the evaluation of terminal location. The results indicated that for the developed agent-based location evaluation model, Yatala was selected as the most appropriate terminal location that results in the highest effectiveness and equity (as measured by level of satisfaction and Gini coefficient, respectively). Other location evaluation models were also used in comparison with the developed agent-based location evaluation model. Those include P-Median, P-Centre, and maximum covering models. It was found that the agent-based location evaluation model outperformed the other location evaluation models. Finally, a sensitivity analysis was conducted in order to evaluate the consistency of model outputs against the uncertainties in the input parameters. In most cases, the terminal location decisions obtained from the developed agent-based location evaluation model was not sensitive to the changes in those parameters. However, the results suggested that when a unit cost of truck travel delay increased, the impact on the final terminal location decisions was observed. This thesis demonstrated the feasibility of applying a decentralised approach to terminal location decision problem using a multi-agent concept and evaluating it against other well-known location problems. A new framework and methodology for the planning of intermodal terminal location evaluation was also formulated. Finally, the problems of terminal location evaluation and optimisation of intermodal freight terminal operation were integrated into a single evaluation model.
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Sirikijpanichkul, Ackchai. "An agent-based location evaluation model." Queensland University of Technology, 2008. http://eprints.qut.edu.au/20672/.

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Truck transportation is considered as a favourable mode by shippers to carry freight at most ranges of distance as it has more flexibility in fleet size, capacity, scheduling, routing, and access. Although truck is considered as the popular mode for freight transportation, road-rail intermodal freight transportation becomes an attractive alternative to road only mode since the latter has no longer assured a reliable service due to traffic congestion problem. It also raises public concern in environmental and road safety impacts. Intermodal freight transportation is defined as a system that carries freight from origin to destination using two or more transportation modes where transfers between modes occur at an intermodal freight terminal. Success of the terminal depends on four major factors, namely: location, efficiency, financial sustainability, and rail level of service. Among these, the location is one of the most crucial success factors and needs to be considered carefully as it has direct and indirect impacts on a number of stakeholders including terminal users, terminal operators, transport network infrastructure providers, and community. Limitations of previous terminal location evaluation models in representing individual preference and behaviour as well as accommodating negotiation and communication between the players bring in an opportunity to develop a new model which is more flexible and capable of providing a solution that is not necessary to be optimal, but acceptable for every player without requiring explicit trade-offs. This thesis is aimed at demonstrating the feasibility of applying an agent-based approach to the evaluation of intermodal freight terminal location and investigating terminal effectiveness against stakeholder equity and some important aspects arising from the different stakeholders’ viewpoints. Agent technologies were introduced to model the stakeholders as individual agents. The agent concept was adopted to develop a decentralised location evaluation system that is able to balance the terminal effectiveness with the stakeholder equity. The proposed agent-based location evaluation model was modelled as a hierarchical control system that comprises three decision levels: local level, stakeholder level and policy level. Policy level is the highest decision level, which is represented by a policy maker. Apart from the policy level, the rest can be viewed as operational decision levels. Local level is the lowest control level. At this level, each stakeholder was classified into stakeholder groups based on their characteristics and interest. The terminal scenarios were then evaluated based on benefit maximisation criteria. Stakeholder control is the higher control level than the local level. It represents the control level where negotiations and decisions between groups of people (stakeholders) with different point of views are made. At this level, negotiation process was used to determine terminal location based on preference and equity of stakeholders. The determined terminal site was then used in the evaluation against constraints to ensure that all agents are satisfied. The terminal location decision for South East Queensland (SEQ) was applied as a case study of this thesis. The SEQ strategic freight transport model was developed, calibrated, and validated to assist in providing inputs for the evaluation of terminal location. The results indicated that for the developed agent-based location evaluation model, Yatala was selected as the most appropriate terminal location that results in the highest effectiveness and equity (as measured by level of satisfaction and Gini coefficient, respectively). Other location evaluation models were also used in comparison with the developed agent-based location evaluation model. Those include P-Median, P-Centre, and maximum covering models. It was found that the agent-based location evaluation model outperformed the other location evaluation models. Finally, a sensitivity analysis was conducted in order to evaluate the consistency of model outputs against the uncertainties in the input parameters. In most cases, the terminal location decisions obtained from the developed agent-based location evaluation model was not sensitive to the changes in those parameters. However, the results suggested that when a unit cost of truck travel delay increased, the impact on the final terminal location decisions was observed. This thesis demonstrated the feasibility of applying a decentralised approach to terminal location decision problem using a multi-agent concept and evaluating it against other well-known location problems. A new framework and methodology for the planning of intermodal terminal location evaluation was also formulated. Finally, the problems of terminal location evaluation and optimisation of intermodal freight terminal operation were integrated into a single evaluation model.
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Books on the topic "Evaluation model"

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McMasters, Alan W. Wholesale provisioning models: Model evaluation. Monterey, California: Naval Postgraduate School, 1986.

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Lafleur, Clay. Program review model. [Barrie, ON]: Simcoe County Board of Education, 1990.

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Pembangunan, Universitas Indonesia Pusat Penelitian Pranata. Studi penyusunan model-model evaluasi hasil pembangunan daerah: Laporan akhir. Jakarta: Pusat Penelitian Pranata Pembangunan, Lembaga Penelitian, Universitas Indonesia, 1999.

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(Firm), Sierra Research. Evaluation of MOBILE vehicle emission model. Washington, D.C: U.S. Department of Transportation, Federal Highway Administration, 1994.

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Planlægningsafdelingen, Denmark Vejdirektoratet, ed. The Danish highway investment evaluation model. Copenhagen, Denmark: Planning Dept., 1992.

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United States. Federal Highway Administration., ed. Evaluation of MOBILE vehicle emission model. [Washington, DC]: U.S. Dept. of Transportation, Federal Highway Administration, 1994.

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1951-, Morris G. E., and Atmospheric Research and Exposure Assessment Laboratory (U.S.), eds. Rocky Mountain acid deposition model assessment model assessment: ARM3 model performance evaluation : project summary. Research Triangle Park, NC: U.S. Environmental Protection Agency, Atmospheric Research and Exposure Assessment Laboratory, 1990.

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Cacina, Nasuh. Test and evaluation of surf forecasting model. Monterey, Calif: Naval Postgraduate School, 1989.

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Kennedy, Thomas L. Southern African transport: An analytical model. Pretoria, South Africa: Africa Institute of South Africa, 1990.

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Amey, Peter. Development and evaluation of a crime management model. London: Home Office Police Research Group, 1996.

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Book chapters on the topic "Evaluation model"

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Cavanagh, Stephen J. "Evaluation." In Orem’s Model in Action, 121–35. London: Macmillan Education UK, 1991. http://dx.doi.org/10.1007/978-1-349-11909-7_8.

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Gass, Saul I. "Model evaluation." In Encyclopedia of Operations Research and Management Science, 518. New York, NY: Springer US, 2001. http://dx.doi.org/10.1007/1-4020-0611-x_629.

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Gettelman, Andrew, and Richard B. Rood. "Model Evaluation." In Earth Systems Data and Models, 161–76. Berlin, Heidelberg: Springer Berlin Heidelberg, 2016. http://dx.doi.org/10.1007/978-3-662-48959-8_9.

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Von Gadow, Klaus, and Gangying Hui. "Model evaluation." In Modelling Forest Development, 181–89. Dordrecht: Springer Netherlands, 1999. http://dx.doi.org/10.1007/978-94-011-4816-0_6.

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Mislevy, Robert J., Geneva Haertel, Michelle Riconscente, Daisy Wise Rutstein, and Cindy Ziker. "Model Evaluation." In Assessing Model-Based Reasoning using Evidence- Centered Design, 71–79. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-52246-3_9.

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Fürnkranz, Johannes, Philip K. Chan, Susan Craw, Claude Sammut, William Uther, Adwait Ratnaparkhi, Xin Jin, et al. "Model Evaluation." In Encyclopedia of Machine Learning, 683. Boston, MA: Springer US, 2011. http://dx.doi.org/10.1007/978-0-387-30164-8_550.

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Aliabadi, Amir A. "Model Evaluation." In Turbulence, 251–58. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-95411-6_19.

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Webb, Geoffrey I. "Model Evaluation." In Encyclopedia of Machine Learning and Data Science, 1–2. New York, NY: Springer US, 2023. http://dx.doi.org/10.1007/978-1-4899-7502-7_555-2.

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Ghayoumi, Mehdi. "Model Evaluation." In Generative Adversarial Networks in Practice, 80–99. Boca Raton: Chapman and Hall/CRC, 2023. http://dx.doi.org/10.1201/9781003281344-3.

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Kakarla, Ramcharan, Sundar Krishnan, and Sridhar Alla. "Model Evaluation." In Applied Data Science Using PySpark, 205–49. Berkeley, CA: Apress, 2020. http://dx.doi.org/10.1007/978-1-4842-6500-0_6.

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Conference papers on the topic "Evaluation model"

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Ulke, Bastian, Friedrich Steimann, and Ralf Lammel. "Partial Evaluation of OCL Expressions." In 2017 ACM/IEEE 20th International Conference on Model-Driven Engineering Languages and Systems (MODELS). IEEE, 2017. http://dx.doi.org/10.1109/models.2017.31.

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Ruiz, Jenny, and Monique Snoeck. "Adapting Kirkpatrick's evaluation model to technology enhanced learning." In MODELS '18: ACM/IEEE 21th International Conference on Model Driven Engineering Languages and Systems. New York, NY, USA: ACM, 2018. http://dx.doi.org/10.1145/3270112.3270114.

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Hegde, V. R. "Impact Evaluation of Interventions for Groundwater Recharge." In River Rejuvenation Kumudvathi Model. The Geological Society of India, 2020. http://dx.doi.org/10.17491/cgsi/2020/156158.

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Sun, Hao, and Oral Büyüköztürk. "Bayesian model updating using incomplete modal data without mode matching." In SPIE Smart Structures and Materials + Nondestructive Evaluation and Health Monitoring, edited by Tribikram Kundu. SPIE, 2016. http://dx.doi.org/10.1117/12.2219300.

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Schmerr, Lester W. "A Localized Multi-Gaussian Ultrasonic Beam Model." In QUANTITATIVE NONDESTRUCTIVE EVALUATION. AIP, 2004. http://dx.doi.org/10.1063/1.1711605.

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Brand, Thomas, and Holger Giese. "Modeling Approach and Evaluation Criteria for Adaptable Architectural Runtime Model Instances." In 2019 ACM/IEEE 22nd International Conference on Model Driven Engineering Languages and Systems (MODELS). IEEE, 2019. http://dx.doi.org/10.1109/models.2019.00006.

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Kim, Hak-Joon. "Model Predictions to the 2005 Ultrasonic Benchmark Problems." In QUANTITATIVE NONDESTRUCTIVE EVALUATION. AIP, 2006. http://dx.doi.org/10.1063/1.2184743.

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Melapudi, Vikram R. "Ray-Rracing Model for Terahertz Imaging of SOFI Inspection." In QUANTITATIVE NONDESTRUCTIVE EVALUATION. AIP, 2006. http://dx.doi.org/10.1063/1.2184566.

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Luo, W. "A Two Dimensional Model for Crack Sizing in Pipes." In QUANTITATIVE NONDESTRUCTIVE EVALUATION. AIP, 2004. http://dx.doi.org/10.1063/1.1711623.

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Garhewal, Bharat, and Carlos Diego N. Damasceno. "An Experimental Evaluation of Conformance Testing Techniques in Active Automata Learning." In 2023 ACM/IEEE 26th International Conference on Model Driven Engineering Languages and Systems (MODELS). IEEE, 2023. http://dx.doi.org/10.1109/models58315.2023.00012.

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Reports on the topic "Evaluation model"

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McKay, S., Nate Richards, and Todd Swannack. Ecological model development : evaluation of system quality. Engineer Research and Development Center (U.S.), September 2022. http://dx.doi.org/10.21079/11681/45380.

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Abstract:
Ecological models are used throughout the US Army Corps of Engineers (USACE) to inform decisions related to ecosystem restoration, water operations, environmental impact assessment, environmental mitigation, and other topics. Ecological models are typically developed in phases of conceptualization, quantification, evaluation, application, and communication. Evaluation is a process for assessing the technical quality, reliability, and ecological basis of a model and includes techniques such as calibration, verification, validation, and review. In this technical note (TN), we describe an approach for evaluating system quality, which generally includes the computational integrity, numerical accuracy, and programming of a model or modeling system. Methods are presented for avoiding computational errors during development, detecting errors through model testing, and updating models based on review and use. A formal structure is proposed for model test plans and subsequently demonstrated for a hypothetical habitat suitability model. Overall, this TN provides ecological modeling practitioners with a rapid guide for evaluating system quality.
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Lu, Ning, and Hong Qiao. Composite Load Model Evaluation. Office of Scientific and Technical Information (OSTI), September 2007. http://dx.doi.org/10.2172/926124.

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Barchet, W. R., R. L. Dennis, S. K. Seilkop, C. M. Banic, D. Davies, R. M. Hoff, A. M. Macdonald, et al. The EMEFS model evaluation. Office of Scientific and Technical Information (OSTI), December 1991. http://dx.doi.org/10.2172/6004604.

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Martin, Paul J. Model Performance and Evaluation. Fort Belvoir, VA: Defense Technical Information Center, September 1997. http://dx.doi.org/10.21236/ada629080.

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Simpson, B. C., and D. J. McCain. Historical model evaluation data requirements. Office of Scientific and Technical Information (OSTI), May 1995. http://dx.doi.org/10.2172/70804.

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Haidvogel, Dale B., and Kate Hedstrom. Ocean Model Evaluation Web Site. Fort Belvoir, VA: Defense Technical Information Center, September 1999. http://dx.doi.org/10.21236/ada629851.

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Haidvogel, Dale B. Ocean Model Evaluation Web Site. Fort Belvoir, VA: Defense Technical Information Center, September 2001. http://dx.doi.org/10.21236/ada625349.

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Edenburn, M. W., M. L. Bunting, and A. C. Jr Payne. CTBT Integrated Verification System Evaluation Model. Office of Scientific and Technical Information (OSTI), October 1997. http://dx.doi.org/10.2172/548603.

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Whiteside, Tad, Thong Hang, and Gregory Flach. Evaluation of help model replacement codes. Office of Scientific and Technical Information (OSTI), July 2009. http://dx.doi.org/10.2172/1237315.

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Foster, K. T. RAS Division model evaluation database tools. Office of Scientific and Technical Information (OSTI), September 1994. http://dx.doi.org/10.2172/10195819.

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