Academic literature on the topic 'Fuzzy set theory'

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Journal articles on the topic "Fuzzy set theory"

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Lehmann, Ingo, Richard Weber, and Hans Jürgen Zimmermann. "Fuzzy set theory." Operations-Research-Spektrum 14, no. 1 (1992): 1–9. http://dx.doi.org/10.1007/bf01783496.

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Zimmermann, H. J. "Fuzzy set theory." Wiley Interdisciplinary Reviews: Computational Statistics 2, no. 3 (2010): 317–32. http://dx.doi.org/10.1002/wics.82.

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Barr, Michael. "Fuzzy Set Theory and Topos Theory." Canadian Mathematical Bulletin 29, no. 4 (1986): 501–8. http://dx.doi.org/10.4153/cmb-1986-079-9.

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AbstractThe relation between the categories of Fuzzy Sets and that of Sheaves is explored and the precise connection between them is explicated. In particular, it is shown that if the notion of fuzzy sets is further fuzzified by making equality (as well as membership) fuzzy, the resultant categories are indeed toposes.
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Takeuti, Gaisi, and Satoko Titani. "Fuzzy logic and fuzzy set theory." Archive for Mathematical Logic 32, no. 1 (1992): 1–32. http://dx.doi.org/10.1007/bf01270392.

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Radu, C., and R. Wilkerson. "Using fuzzy set theory." IEEE Potentials 14, no. 5 (1996): 33–35. http://dx.doi.org/10.1109/45.481510.

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Anjan, Mukherjee1 and Ajoy Kanti Das2. "On Fuzzy Soft Multi Set and Its Application in Information Systems." International Journal of Computer-Aided Technologies (IJCAx) 02, Jul (2015): 01–18. https://doi.org/10.5121/ijcax.2015.2303.

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Research on information and communication technologies have been developed rapidly since it can be applied easily to several areas like computer science, medical science, economics, environments, engineering, among other. Applications of soft set theory, especially in information systems have been found paramount importance. Recently, Mukherjee and Das defined some new operations in fuzzy soft multi set theory and show that the De-Morgan’s type of results hold in fuzzy soft multi set theory with respect to these newly defined operations. In this paper, we extend their work and study some
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Anjan, Mukherjee1 and Ajoy Kanti Das2. "On Fuzzy Soft Multi Set and Its Application in Information Systems." International Journal of Computer-Aided technologies (IJCAx) 2, no. 3 (2023): 29. https://doi.org/10.5281/zenodo.8256282.

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Research on information and communication technologies have been developed rapidly since it can be applied easily to several areas like computer science, medical science, economics, environments, engineering, among other. Applications of soft set theory, especially in information systems have been found paramount importance. Recently, Mukherjee and Das defined some new operations in fuzzy soft multi set theory and show that the De-Morgan’s type of results hold in fuzzy soft multi set theory with respect to these newly defined operations. In this paper, we extend their work and study some
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Hajek, P., and Z. Hanikova. "Interpreting lattice-valued set theory in fuzzy set theory." Logic Journal of IGPL 21, no. 1 (2012): 77–90. http://dx.doi.org/10.1093/jigpal/jzs023.

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GAO, XIAOYU, Q. S. GAO, Y. HU, and L. LI. "A PROBABILITY-LIKE NEW FUZZY SET THEORY." International Journal of Pattern Recognition and Artificial Intelligence 20, no. 03 (2006): 441–62. http://dx.doi.org/10.1142/s0218001406004697.

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In this paper, the reasons for the shortcoming of Zadeh's fuzzy set theory — it cannot correctly reflect different kinds of fuzzy phenomenon in the natural world — are discussed. In addition, the proof of the error of Zadeh's fuzzy set theory — it incorrectly defined the set complement that cannot exist in Zadeh's fuzzy set theory — is proposed. This error of Zadeh's fuzzy set theory causes confusion in thinking, logic and conception. It causes the seriously mistaken belief that logics of fuzzy sets necessarily go against classical and normal thinking, logic and conception. Two new fuzzy set t
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Soni, Manjula. "Fuzzy Set Theory in Sociology." International Journal for Research in Applied Science and Engineering Technology V, no. IX (2017): 1148–51. http://dx.doi.org/10.22214/ijraset.2017.9165.

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Dissertations / Theses on the topic "Fuzzy set theory"

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Mao, Hongwei. "Estimating labour productivity using fuzzy set theory." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1999. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape8/PQDD_0019/MQ47065.pdf.

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Raghfar, Hossein. "Application of fuzzy set theory to poverty analysis." Thesis, University of Essex, 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.343582.

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Saboo, Jai Vardhan. "An investment analysis model using fuzzy set theory." Thesis, Virginia Polytechnic Institute and State University, 1989. http://hdl.handle.net/10919/50087.

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Traditional methods for evaluating investments in state-of-the-art technology are sometimes found lacking in providing equitable recommendations for project selection. The major cause for this is the inability of these methods to handle adequately uncertainty and imprecision, and account for every aspect of the project, economic and non-economic, tangible and intangible. Fuzzy set theory provides an alternative to probability theory for handling uncertainty, while at the same time being able to handle imprecision. It also provides a means of closing the gap between the human thought process an
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Bhattacharyya, Kakali. "Classification of rock masses based on fuzzy set theory." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2003. http://hub.hku.hk/bib/B29490352.

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Murali, V. "A study of universal algebras in fuzzy set theory." Thesis, Rhodes University, 1988. http://hdl.handle.net/10962/d1001983.

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This thesis attempts a synthesis of two important and fast developing branches of mathematics, namely universal algebra and fuzzy set theory. Given an abstract algebra [X,F] where X is a non-empty set and F is a set of finitary operations on X, a fuzzy algebra [I×,F] is constructed by extending operations on X to that on I×, the set of fuzzy subsets of X (I denotes the unit interval), using Zadeh's extension principle. Homomorphisms between fuzzy algebras are defined and discussed. Fuzzy subalgebras of an algebra are defined to be elements of a fuzzy algebra which respect the extended algebra
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Assi, Jolnar Abdulkarim. "Knightian uncertainty modelling and its impact on option pricing : applications of fuzzy set theory, fuzzy measure theory and fuzzy differential calculus." Thesis, City University London, 2003. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.274460.

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Peters, Barry. "Stable fuzzy logic controllers for uncertain dynamic systems." Thesis, Georgia Institute of Technology, 1993. http://hdl.handle.net/1853/18223.

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Melik, Serhat. "Cash Flow Analysis Of Construction Projects Using Fuzzy Set Theory." Master's thesis, METU, 2010. http://etd.lib.metu.edu.tr/upload/12612517/index.pdf.

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Construction industry is a one of the most risky sectors due to high level of uncertainties included in the nature of the construction projects. Although there are many reasons, the deficiency of cash is one of the main factors threatening the success of the construction projects and causing business failures. Therefore, an appropriate cash planning technique is necessary for adequate cost control and efficient cash management while considering the risks and uncertainties of the construction projects. The main objective of this thesis is to develop a realistic, reliable and cost-schedule inte
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Al-Zaidan, Amina S. "Mathematical modeling of marine environment contamination using fuzzy set theory." Thesis, Bangor University, 2002. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.248901.

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Almadani, Firdos Mohammed. "Modelling and analysing vague geographical places using fuzzy set theory." Thesis, University of Leicester, 2016. http://hdl.handle.net/2381/37352.

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Vagueness is an essential part of how humans perceive and understand the geographical world they occupy. It has now become of increasing important to acknowledge this situation in geographical databases and analyses in the field of Geographical Information Science (GIScience). This research has tackled the wholly original topic of modelling vague geographical places (objects) based on fuzzy set theory with a view to assessing the implications of routing problem around those vague places. The research has focused on the modelling of vague places, for a number of villages and rural settlements,
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Books on the topic "Fuzzy set theory"

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Lowen, R. Fuzzy Set Theory. Springer Netherlands, 1996. http://dx.doi.org/10.1007/978-94-015-8741-9.

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Smithson, Michael, and Jay Verkuilen. Fuzzy Set Theory. SAGE Publications, Inc., 2006. http://dx.doi.org/10.4135/9781412984300.

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Zimmermann, H. J. Fuzzy set theory--and its applications. 2nd ed. Kluwer Academic Publishers, 1991.

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Cornelis, Chris, Glad Deschrijver, Mike Nachtegael, Steven Schockaert, and Yun Shi, eds. 35 Years of Fuzzy Set Theory. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-16629-7.

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Zimmermann, H. J. Fuzzy Set Theory—and Its Applications. Springer Netherlands, 1996. http://dx.doi.org/10.1007/978-94-015-8702-0.

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Zimmermann, H. J. Fuzzy Set Theory — and Its Applications. Springer Netherlands, 1991. http://dx.doi.org/10.1007/978-94-015-7949-0.

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Zimmermann, H. J. Fuzzy Set Theory—and Its Applications. Springer Netherlands, 2001. http://dx.doi.org/10.1007/978-94-010-0646-0.

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Zimmermann, H. J. Fuzzy Set Theory — and Its Applications. Springer Netherlands, 1985. http://dx.doi.org/10.1007/978-94-015-7153-1.

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H, St Clair Ute, and Yuan Bo, eds. Fuzzy set theory: Foundations and applications. Prentice Hall, 1997.

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Zimmermann, H. J. Fuzzy Set Theory - and Its Applications. Springer Netherlands, 1991.

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Book chapters on the topic "Fuzzy set theory"

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Gottwald, Siegfried. "Basic fuzzy set theory." In Fuzzy Sets and Fuzzy Logic. Vieweg+Teubner Verlag, 1993. http://dx.doi.org/10.1007/978-3-322-86812-1_2.

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Lowen, R. "Elementary Set Theory." In Fuzzy Set Theory. Springer Netherlands, 1996. http://dx.doi.org/10.1007/978-94-015-8741-9_1.

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Klement, Erich Peter, Radko Mesiar, and Endre Pap. "Fuzzy set theory." In Trends in Logic. Springer Netherlands, 2000. http://dx.doi.org/10.1007/978-94-015-9540-7_12.

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Mordeson, John N., Mark J. Wierman, Terry D. Clark, Alex Pham, and Michael A. Redmond. "Fuzzy Set Theory." In Linear Models in the Mathematics of Uncertainty. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-35224-9_1.

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Krejčí, Jana. "Fuzzy Set Theory." In Pairwise Comparison Matrices and their Fuzzy Extension. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-77715-3_3.

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Shanahan, James G. "Fuzzy Set Theory." In Soft Computing for Knowledge Discovery. Springer US, 2000. http://dx.doi.org/10.1007/978-1-4615-4335-0_3.

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Ebrahimnejad, Ali, and José Luis Verdegay. "Fuzzy Set Theory." In Fuzzy Sets-Based Methods and Techniques for Modern Analytics. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-73903-8_1.

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Xu, Jiuping, and Xiaoyang Zhou. "Fuzzy Set Theory." In Fuzzy-Like Multiple Objective Decision Making. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-16895-6_1.

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Werro, Nicolas. "Fuzzy Set Theory." In Fuzzy Classification of Online Customers. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-15970-6_2.

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Lai, Young-Jou, and Ching-Lai Hwang. "Fuzzy Set Theory." In Lecture Notes in Economics and Mathematical Systems. Springer Berlin Heidelberg, 1992. http://dx.doi.org/10.1007/978-3-642-48753-8_2.

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Conference papers on the topic "Fuzzy set theory"

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Alkhazaleh, Shawkat. "n-valued refined neutrosophic soft set theory." In 2016 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). IEEE, 2016. http://dx.doi.org/10.1109/fuzz-ieee.2016.7738004.

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"FUZZY SET THEORY BASED STUDENT EVALUATION." In International Conference on Fuzzy Computation. SciTePress - Science and and Technology Publications, 2009. http://dx.doi.org/10.5220/0002312300530058.

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Medynskaya, M. K. "Fuzzy set theory. The concept of fuzzy sets." In 2015 XVIII International Conference on Soft Computing and Measurements (SCM). IEEE, 2015. http://dx.doi.org/10.1109/scm.2015.7190402.

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Hossein Zadeh, Parisa D., and Marek Z. Reformat. "Feature-based similarity assessment in ontology using fuzzy set theory." In 2012 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). IEEE, 2012. http://dx.doi.org/10.1109/fuzz-ieee.2012.6251266.

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Szmidt, E., and J. F. Baldwin. "Intuitionistic Fuzzy Set Functions, Mass Assignment Theory, Possibility Theory and Histograms." In 2006 IEEE International Conference on Fuzzy Systems. IEEE, 2006. http://dx.doi.org/10.1109/fuzzy.2006.1681691.

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Ming-Chun Wang, Zheng-Ou Wang, Ming Zhang, and Peng Yan. "Decision rule extraction method based on rough set theory and fuzzy set theory." In Proceedings of 2005 International Conference on Machine Learning and Cybernetics. IEEE, 2005. http://dx.doi.org/10.1109/icmlc.2005.1527312.

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Azar, Ahmad Taher, Nidhal Bouaynaya, and Robi Polikar. "Inductive learning based on rough set theory for medical decision making." In 2015 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). IEEE, 2015. http://dx.doi.org/10.1109/fuzz-ieee.2015.7338075.

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Wierman, M. J. "Yet another axiomization of fuzzy set theory." In IEEE Annual Meeting of the Fuzzy Information, 2004. Processing NAFIPS '04. IEEE, 2004. http://dx.doi.org/10.1109/nafips.2004.1336289.

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Saeed, Faisel, K. M. George, and Huizhu Lu. "Image contrast enhancement using fuzzy set theory." In the 1992 ACM/SIGAPP Symposium. ACM Press, 1992. http://dx.doi.org/10.1145/143559.143668.

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Xia, Xintao, Zhongyu Wang, and Yongsheng Gao. "Optimal measurement planning using fuzzy-set theory." In Fifth International Symposium on Instrumentation and Control Technology, edited by Guangjun Zhang, Huijie Zhao, and Zhongyu Wang. SPIE, 2003. http://dx.doi.org/10.1117/12.521921.

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Reports on the topic "Fuzzy set theory"

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Gluckman, Albert G., and Aivars Celmins. Cost Effectiveness Analysis Using Fuzzy Set Theory. Defense Technical Information Center, 1993. http://dx.doi.org/10.21236/ada274003.

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Esteva, Francesc. On Negations and Algebras in Fuzzy Set Theory. Defense Technical Information Center, 1986. http://dx.doi.org/10.21236/ada604012.

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Goodman, I. R., and V. M. Bier. A Re-Examination of the Relationship between Fuzzy Set Theory and Probability Theory. Defense Technical Information Center, 1991. http://dx.doi.org/10.21236/ada240243.

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Tsidylo, Ivan M., Serhiy O. Semerikov, Tetiana I. Gargula, Hanna V. Solonetska, Yaroslav P. Zamora, and Andrey V. Pikilnyak. Simulation of intellectual system for evaluation of multilevel test tasks on the basis of fuzzy logic. CEUR Workshop Proceedings, 2021. http://dx.doi.org/10.31812/123456789/4370.

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The article describes the stages of modeling an intelligent system for evaluating multilevel test tasks based on fuzzy logic in the MATLAB application package, namely the Fuzzy Logic Toolbox. The analysis of existing approaches to fuzzy assessment of test methods, their advantages and disadvantages is given. The considered methods for assessing students are presented in the general case by two methods: using fuzzy sets and corresponding membership functions; fuzzy estimation method and generalized fuzzy estimation method. In the present work, the Sugeno production model is used as the closest
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Willson. L51756 State of the Art Intelligent Control for Large Engines. Pipeline Research Council International, Inc. (PRCI), 1996. http://dx.doi.org/10.55274/r0010423.

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Computers have become a vital part of the control of pipeline compressors and compressor stations. For many tasks, computers have helped to improve accuracy, reliability, and safety, and have reduced operating costs. Computers excel at repetitive, precise tasks that humans perform poorly - calculation, measurement, statistical analysis, control, etc. Computers are used to perform these type of precise tasks at compressor stations: engine / turbine speed control, ignition control, horsepower estimation, or control of complicated sequences of events during startup and/or shutdown. For other task
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