Bibliographies thématiques / Analysis criteria

Littérature scientifique sur le sujet « Analysis criteria »

Auteur : Grafiati
Publié le 14 mars 2023

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Consultez les listes thématiques d’articles de revues, de livres, de thèses, de rapports de conférences et d’autres sources académiques sur le sujet « Analysis criteria ».

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Articles de revues sur le sujet "Analysis criteria"

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Jaini, Nor I., et Sergei V. Utyuzhnikov. « Critical Criterion Analysis for Multi-criteria Decision Making ». International Journal of Applied Physics and Mathematics 6, no 3 (2016) : 129–37. http://dx.doi.org/10.17706/ijapm.2016.6.3.129-137.

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Jagadeesh, Chintu, et K. Srinivasa Rao. « Analysis of Thermal Criteria on Cryogenic Pressure Vessel ». International Journal of Trend in Scientific Research and Development Volume-3, Issue-2 (28 février 2019) : 205–8. http://dx.doi.org/10.31142/ijtsrd20307.

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Nuthall, P. L. « MULTIPLE CRITERIA ANALYSIS ». Agricultural Economics 5, no 2 (juin 1991) : 174–78. http://dx.doi.org/10.1111/j.1574-0862.1991.tb00147.x.

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Bernal-González, Luis, et Manuel Ordóñez Cabrera. « Lineability criteria, with applications ». Journal of Functional Analysis 266, no 6 (mars 2014) : 3997–4025. http://dx.doi.org/10.1016/j.jfa.2013.11.014.

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Futorny, Vyacheslav, Vladimir V. Sergeichuk et Nadya Zharko. « Positivity Criteria Generalizing the Leading Principal Minors Criterion ». Positivity 11, no 1 (13 octobre 2006) : 191–99. http://dx.doi.org/10.1007/s11117-006-2013-2.

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Watkins, Marley W. « Determining Parallel Analysis Criteria ». Journal of Modern Applied Statistical Methods 5, no 2 (1 novembre 2005) : 344–46. http://dx.doi.org/10.22237/jmasm/1162354020.

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Flores, Benito E., et D. Clay Whybark. « Multiple Criteria ABC Analysis ». International Journal of Operations & ; Production Management 6, no 3 (mars 1986) : 38–46. http://dx.doi.org/10.1108/eb054765.

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Kuo, Chen-Ming, et Chih-Chiang Lin. « Analysis of derailment criteria ». Proceedings of the Institution of Mechanical Engineers, Part F : Journal of Rail and Rapid Transit 230, no 4 (29 avril 2015) : 1158–63. http://dx.doi.org/10.1177/0954409715583692.

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Arioli, Mario, Iain Duff et Daniel Ruiz. « Stopping Criteria for Iterative Solvers ». SIAM Journal on Matrix Analysis and Applications 13, no 1 (janvier 1992) : 138–44. http://dx.doi.org/10.1137/0613012.

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Schreiber, Sebastian J. « Criteria for Cr Robust Permanence ». Journal of Differential Equations 162, no 2 (avril 2000) : 400–426. http://dx.doi.org/10.1006/jdeq.1999.3719.

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Thèses sur le sujet "Analysis criteria"

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Morris-Oswald, Monica. « Social criteria for multi-criteria decision analysis in flood management ». Thesis, National Library of Canada = Bibliothèque nationale du Canada, 2001. http://www.collectionscanada.ca/obj/s4/f2/dsk3/ftp04/MQ57562.pdf.

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Yates, Rebekah. « Norm-preserving criteria for uniform algebra isomorphisms ». Diss., [Missoula, Mont.] : The University of Montana, 2009. http://etd.lib.umt.edu/theses/available/etd-06042009-133437.

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Treitz, Martin. « Production process design using multi-criteria analysis ». Karlsruhe : Univ.-Verl. Karlsruhe, 2006. http://www.uvka.de/univerlag/volltexte/2006/178/.

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Anil, Kivanc A. « Multi-criteria analysis in naval ship design ». Thesis, Monterey California. Naval Postgraduate School, 2005. http://hdl.handle.net/10945/2325.

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Approved for public release, distribution is unlimited
Numerous optimization problems involve systems with multiple and often contradictory criteria. Such contradictory criteria have been an issue for marine/naval engineering design studies for many years. This problem becomes more important when one considers novel ship types with very limited or no operational record. A number of approaches have been proposed to overcome these multiple criteria design optimization problems. This Thesis follows the Parameter Space Investigation (PSI) technique to address these problems. The PSI method is implemented with a software package called MOVI (Multi-criteria Optimization and Vector Identification). Two marine/naval engineering design optimization models were investigated using the PSI technique along with the MOVI software. The first example was a bulk carrier design model which was previously studied with other optimization methods. This model, which was selected due to its relatively small dimensionality and the availability of existing studies, was utilized in order to demonstrate and validate the features of the proposed approach. A more realistic example was based on the "MIT Functional Ship Design Synthesis Model" with a greater number of parameters, criteria, and functional constraints. A series of optimization studies conducted for this model demonstrated that the proposed approach can be implemented in a naval ship design environment and can lead to a large design parameter space exploration with minimum computational effort.
Lieutenant Junior Grade, Turkish Navy
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Butler, John Christopher. « Simulation analysis of multi-criteria decision models / ». Digital version accessible at:, 1998. http://wwwlib.umi.com/cr/utexas/main.

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Anil, Kivanc Ali. « Multi-criteria analysis in Naval Ship Design / ». Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 2005. http://library.nps.navy.mil/uhtbin/hyperion/05Mar%5FAnil.pdf.

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Thesis (M.S. in Mechanical Engineering)--Naval Postgraduate School, March 2005.
Thesis Advisor(s): Fotis Papoulias, Roman B. Statnikov. Includes bibliographical references (p. 241). Also available online.
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Kilminster, Devin. « Modelling dynamical systems via behaviour criteria ». University of Western Australia. Dept. of Mathematics and Statistics, 2002. http://theses.library.uwa.edu.au/adt-WU2003.0029.

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An important part of the study of dynamical systems is the fitting of models to time-series data. That is, given the data, a series of observations taken from a (not fully understood) system of interest, we would like to specify a model, a mathematical system which generates a sequence of “simulated” observations. Our aim is to obtain a “good” model — one that is in agreement with the data. We would like this agreement to be quantitative — not merely qualitative. The major subject of this thesis is the question of what good quantitative agreement means. Most approaches to this question could be described as “predictionist”. In the predictionist approach one builds models by attempting to answer the question, “given that the system is now here, where will it be next?” The quality of the model is judged by the degree to which the states of the model and the original system agree in the near future, conditioned on the present state of the model agreeing with that of the original system. Equivalently, the model is judged on its ability to make good short-term predictions on the original system. The main claim of this thesis is that prediction is often not the most appropriate criterion to apply when fitting models. We show, for example, that one can have models that, while able to make good predictions, have long term (or free-running) behaviour bearing little resemblance to that exhibited in the original time-series. We would hope to be able to use our models for a wide range of purposes other than just prediction — certainly we would like our models to exhibit good free-running behaviour. This thesis advocates a “behaviourist” approach, in which the criterion for a good model is that its long-term behaviour matches that exhibited by the data. We suggest that the behaviourist approach enjoys a certain robustness over the predictionist approaches. We show that good predictors can often be very poorly behaved, and suggest that well behaved models cannot perform too badly at the task of prediction. The thesis begins by comparing the predictionist and behaviourist approaches in the context of a number of simplified model-building problems. It then presents a simple theory for the understanding of the differences between the two approaches. Effective methods for the construction of well-behaved models are presented. Finally, these methods are applied to two real-world problems — modelling of the response of a voltage-clamped squid “giant” axon, and modelling of the “yearly sunspot number”.
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Bremner, Alexandra P. « Localised splitting criteria for classification and regression trees ». Thesis, Bremner, Alexandra P. (2004) Localised splitting criteria for classification and regression trees. PhD thesis, Murdoch University, 2004. https://researchrepository.murdoch.edu.au/id/eprint/440/.

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This thesis presents a modification of existing entropy-based splitting criteria for classification and regression trees. Trees are typically grown using splitting criteria that choose optimal splits without taking future splits into account. This thesis examines localised splitting criteria that are based on local averaging in regression trees or local proportions in classification trees. The use of a localised criterion is motivated by the fact that future splits result in leaves that contain local observations, and hence local deviances provide a better approximation of the deviance of the fully grown tree. While most recent research has focussed on tree-averaging techniques that are aimed at taking a moderately successful splitting criterion and improving its predictive power, this thesis concentrates on improving the splitting criterion. Use of a localised splitting criterion captures local structures and enables later splits to capitalise on the placement of earlier splits when growing a tree. Using the localised splitting criterion results in much simpler trees for pure interaction data (data with no main effects) and can produce trees with fewer errors and lower residual mean deviances than those produced using a global splitting criterion when applied to real data sets with strong interaction effects. The superiority of the localised splitting criterion can persist when multiple trees are grown and averaged using simple methods. Although a single tree grown using the localised splitting criterion can outperform tree averaging using the global criterion, generally improvements in predictive performance are achieved by utilising the localised splitting criterion's property of detecting local discontinuities and averaging over sets of trees grown by placing splits where the deviance is locally minimal. Predictive performance improves further when the degree of localisation of the splitting criterion is randomly selected and weighted randomisation is used with locally minimal deviances to produce sets of trees to average over. Although state of the art methods quickly average very large numbers of trees, thus making the performance of the splitting criterion less critical, predictive performance when the localised criterion is used in bagging indicates that different splitting methods warrant investigation. The localised splitting criterion is most useful for growing one tree or a small number of trees to examine structure in the data. Structurally different trees can be obtained by simply splitting the data where the localised splitting criterion is locally optimal.
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Bremner, Alexandra P. « Localised splitting criteria for classification and regression trees / ». Access via Murdoch University Digital Theses Project, 2004. http://wwwlib.murdoch.edu.au/adt/browse/view/adt-MU20040606.142949.

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Chen, Ye. « Multiple Criteria Decision Analysis : Classification Problems and Solutions ». Thesis, University of Waterloo, 2006. http://hdl.handle.net/10012/2892.

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Multiple criteria decision analysis (MCDA) techniques are developed to address challenging classification problems arising in engineering management and elsewhere. MCDA consists of a set of principles and tools to assist a decision maker (DM) to solve a decision problem with a finite set of alternatives compared according to two or more criteria, which are usually conflicting. The three types of classification problems to which original research contributions are made are
  1. Screening: Reduce a large set of alternatives to a smaller set that most likely contains the best choice.
  2. Sorting: Arrange the alternatives into a few groups in preference order, so that the DM can manage them more effectively.
  3. Nominal classification: Assign alternatives to nominal groups structured by the DM, so that the number of groups, and the characteristics of each group, seem appropriate to the DM.
Research on screening is divided into two parts: the design of a sequential screening procedure that is then applied to water resource planning in the Region of Waterloo, Ontario, Canada; and the development of a case-based distance method for screening that is then demonstrated using a numerical example.

Sorting problems are studied extensively under three headings. Case-based distance sorting is carried out with Model I, which is optimized for use with cardinal criteria only, and Model II, which is designed for both cardinal and ordinal criteria; both sorting approaches are applied to a case study in Canadian municipal water usage analysis. Sorting in inventory management is studied using a case-based distance method designed for multiple criteria ABC analysis, and then applied to a case study involving hospital inventory management. Finally sorting is applied to bilateral negotiation using a case-based distance model to assist negotiators that is then demonstrated on a negotiation regarding the supply of bicycle components.

A new kind of decision analysis problem, called multiple criteria nominal classification (MCNC), is addressed. Traditional classification methods in MCDA focus on sorting alternatives into groups ordered by preference. MCNC is the classification of alternatives into nominal groups, structured by the DM, who specifies multiple characteristics for each group. The features, definitions and structures of MCNC are presented, emphasizing criterion and alternative flexibility. An analysis procedure is proposed to solve MCNC problems systematically and applied to a water resources planning problem.
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Livres sur le sujet "Analysis criteria"

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Linkov, Igor, Emily Moberg, Benjamin D. Trump, Boris Yatsalo et Jeffrey M. Keisler. Multi-Criteria Decision Analysis. Second edition. | Boca Raton : CRC Press, 2020. | : CRC Press, 2020. http://dx.doi.org/10.1201/9780429326448.

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Ishizaka, Alessio, et Philippe Nemery. Multi-Criteria Decision Analysis. Chichester, UK : John Wiley & Sons Ltd, 2013. http://dx.doi.org/10.1002/9781118644898.

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Greco, Salvatore, Matthias Ehrgott et José Rui Figueira, dir. Multiple Criteria Decision Analysis. New York, NY : Springer New York, 2016. http://dx.doi.org/10.1007/978-1-4939-3094-4.

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Belton, Valerie, et Theodor J. Stewart. Multiple Criteria Decision Analysis. Boston, MA : Springer US, 2002. http://dx.doi.org/10.1007/978-1-4615-1495-4.

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Hageman, John P. Repository operational criteria analysis. Washington, DC : Division of High-Level Waste Management, Office of Nuclear Material Safety and Safeguards, U.S. Nuclear Regulatory Commission, 1992.

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Gul, Muhammet, Melih Yucesan et Melike Erdogan. Multi-Criteria Decision Analysis. Boca Raton : CRC Press, 2022. http://dx.doi.org/10.1201/9781003212904.

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International Conference on MCDM (11th 1994 Coimbra, Portugal). Multicriteria analysis. New York : Springer-Verlag, 1997.

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Hageman, John P. Repository operational criteria comparative analysis. Washington, DC : Division of Waste Management, Office of Nuclear Material Safety and Safeguards, U.S. Nuclear Regulatory Commission, 1994.

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Great Britain. Department of the Environment, Transport and the Regions., dir. Multi-criteria analysis : A manual. London : Department of the Environment, Transport and the Regions, 2000.

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1948-, Kitagawa G., dir. Information criteria and statistical modeling. New York : Springer, 2008.

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Chapitres de livres sur le sujet "Analysis criteria"

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Mateo, José Ramón San Cristóbal. « Multi-Criteria Analysis ». Dans Multi Criteria Analysis in the Renewable Energy Industry, 7–10. London : Springer London, 2012. http://dx.doi.org/10.1007/978-1-4471-2346-0_2.

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Talhofer, Václav, Šárka Hošková-Mayerová et Alois Hofmann. « Multi-criteria Analysis ». Dans Quality of Spatial Data in Command and Control System, 39–48. Cham : Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-94562-0_3.

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Mishan, E. J., et Euston Quah. « Crude investment criteria ». Dans Cost-Benefit Analysis, 111–14. Sixth edition. | Milton Park, Abingdon, Oxon ; New York : Routledge, 2020. : Routledge, 2020. http://dx.doi.org/10.4324/9781351029780-22.

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Curry, Steve, et John Weiss. « Project Criteria ». Dans Project Analysis in Developing Countries, 41–70. London : Palgrave Macmillan UK, 2000. http://dx.doi.org/10.1057/9780230375116_3.

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Jain, Satish Kumar. « Efficiency Criteria ». Dans Economic Analysis of Liability Rules, 23–33. New Delhi : Springer India, 2014. http://dx.doi.org/10.1007/978-81-322-2029-9_2.

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Curry, Steve, et John Weiss. « Project Criteria ». Dans Project Analysis in Developing Countries, 44–73. London : Palgrave Macmillan UK, 1993. http://dx.doi.org/10.1057/9780230378506_3.

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Javidinejad, Amir. « Failure Criteria ». Dans Essentials of Mechanical Stress Analysis, 59–67. 2e éd. Boca Raton : CRC Press, 2023. http://dx.doi.org/10.1201/9781003311218-4.

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Huguenin, Jean-Marc. « Data Envelopment Analysis ». Dans Multi-Criteria Decision Analysis, 235–74. Chichester, UK : John Wiley & Sons Ltd, 2013. http://dx.doi.org/10.1002/9781118644898.ch10.

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Moshkovich, Helen, Alexander Mechitov et David Olson. « Verbal Decision Analysis ». Dans Multiple Criteria Decision Analysis, 605–36. New York, NY : Springer New York, 2016. http://dx.doi.org/10.1007/978-1-4939-3094-4_15.

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Belton, Valerie, et Theodor J. Stewart. « The Multiple Criteria Problem ». Dans Multiple Criteria Decision Analysis, 13–33. Boston, MA : Springer US, 2002. http://dx.doi.org/10.1007/978-1-4615-1495-4_2.

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Actes de conférences sur le sujet "Analysis criteria"

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Budhakooncharoen, S., et B. Dhabhisara. « Determination of the weighting factors of criteria influencing highway flooding using Multi Criteria Analysis based on an Analytic Hierarchy Process ». Dans RISK ANALYSIS 2014. Southampton, UK : WIT Press, 2014. http://dx.doi.org/10.2495/risk140381.

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Alzabut, J. « Oscillation Criteria for Second Order Impulsive Delay Differential Equation ». Dans GLOBAL ANALYSIS AND APPLIED MATHEMATICS : International Workshop on Global Analysis. AIP, 2004. http://dx.doi.org/10.1063/1.1814745.

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Begault, Durand R., Heather D. Heise et Christopher A. Peltier. « Analysis criteria for forensic musicology ». Dans ICA 2013 Montreal. ASA, 2013. http://dx.doi.org/10.1121/1.4799479.

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Guarascio, M., M. Lombardi, G. Rossi et G. Sciarra. « Risk analysis and acceptability criteria ». Dans SAFE 2007. Southampton, UK : WIT Press, 2007. http://dx.doi.org/10.2495/safe070131.

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Demidenko, Eugene, Theodore E. Simos, George Psihoyios et Ch Tsitouras. « Criteria for Unconstrained Global Optimization in Nonconvex Problems ». Dans Numerical Analysis and Applied Mathematics. AIP, 2007. http://dx.doi.org/10.1063/1.2790094.

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Sasena, Michael, Panos Papalambros et Pierre Goovaerts. « Metamodeling sampling criteria in a global optimization framework ». Dans 8th Symposium on Multidisciplinary Analysis and Optimization. Reston, Virigina : American Institute of Aeronautics and Astronautics, 2000. http://dx.doi.org/10.2514/6.2000-4921.

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Mackman, Thomas, et Christian Allen. « Aerodynamic Data Modeling Using Multi-Criteria Adaptive Sampling ». Dans 13th AIAA/ISSMO Multidisciplinary Analysis Optimization Conference. Reston, Virigina : American Institute of Aeronautics and Astronautics, 2010. http://dx.doi.org/10.2514/6.2010-9194.

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Fook, Chan Yuen, Gurnam Kaur Sidhu, Rosna Awang Hashim, Azma Abd Hamid et Farhana Wan Yunus. « Effective criteria of item analysis software ». Dans 2014 IEEE 6th Conference on Engineering Education (ICEED). IEEE, 2014. http://dx.doi.org/10.1109/iceed.2014.7194696.

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Royer, Michael. « Analysis of color rendition specification criteria ». Dans Light-Emitting Devices, Materials, and Applications, sous la direction de Martin Strassburg, Jong Kyu Kim et Michael R. Krames. SPIE, 2019. http://dx.doi.org/10.1117/12.2507283.

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Morandini, Cedric, Franck Legerstee et Johan Mombaerts. « Criteria for Analysis of Offloading Operation ». Dans Offshore Technology Conference. Offshore Technology Conference, 2002. http://dx.doi.org/10.4043/14311-ms.

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Rapports d'organisations sur le sujet "Analysis criteria"

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Hageman, J. P., et A. H. Chowdhury. Repository operational criteria comparative analysis. Office of Scientific and Technical Information (OSTI), juin 1994. http://dx.doi.org/10.2172/10161388.

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Black, Paul E., et Athos Ribiero. SATE V Ockham Sound Analysis Criteria. National Institute of Standards and Technology, mars 2016. http://dx.doi.org/10.6028/nist.ir.8113.

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Black, Paul E., et Kanwardeep Singh Walia. SATE VI Ockham Sound Analysis Criteria. National Institute of Standards and Technology, mai 2020. http://dx.doi.org/10.6028/nist.ir.8304.

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Chinn, Maryjo. Realism in young adult literature : criteria and analysis. Portland State University Library, janvier 2000. http://dx.doi.org/10.15760/etd.5376.

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Linke, Ethan, Nazmina Mahmoudzadeh et Darren Holland. Prioritising Foodborne Disease with Multi-Criteria Decision Analysis. Food Standards Agency, novembre 2021. http://dx.doi.org/10.46756/sci.fsa.gex408.

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In recent years, the FSA has published a series of research projects which have produced estimates of the frequency and burden of thirteen different foodborne diseases. This document outlines the methodology and results of a multi-criteria decision analysis (MCDA) used to rank them in order of their detrimental effect on UK society.
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Alliger, George M., Scott I. Tamnenbaum, Winston Bennett, Traver Jr., Shotland Holly et Allison. A Meta-Analysis of the Relations among Training Criteria. Fort Belvoir, VA : Defense Technical Information Center, mai 1998. http://dx.doi.org/10.21236/ada368508.

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Shaukat, S. K., et N. C. Chokshi. Regulatory analysis for USI A-40, Seismic Design Criteria''. Office of Scientific and Technical Information (OSTI), septembre 1989. http://dx.doi.org/10.2172/5687807.

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Banks, H. T., Kathleen J. Holm et Franz Kappel. A Monte Carlo Based Analysis of Optimal Design Criteria. Fort Belvoir, VA : Defense Technical Information Center, novembre 2011. http://dx.doi.org/10.21236/ada556942.

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Gerdes, John W., et Eric Spero. A Compact Review of Multi-criteria Decision Analysis Uncertainty Techniques. Fort Belvoir, VA : Defense Technical Information Center, février 2013. http://dx.doi.org/10.21236/ada582195.

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Kuswa, Glenn W., Jeffrey Yeenien Tsao, Thomas E. Drennen, Jason V. Zuffranieri, Orman Henrie Paananen, Scott A. Jones, Juergen G. Ortner, Jeffrey D. Brewer et Maximo M. Valdez. Multi-attribute criteria applied to electric generation energy system analysis LDRD. Office of Scientific and Technical Information (OSTI), octobre 2005. http://dx.doi.org/10.2172/923152.

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