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Books on the topic 'Fuzzy logic set'

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Published: 2 June 2025

Last updated: 22 June 2025

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1

Novák, Vilém. Mathematical principles of fuzzy logic. Kluwer Academic, 1999.

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2

Nguyen, Hung T. A first course in fuzzy logic. 2nd ed. Chapman & Hall, 2000.

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3

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

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4

Ruan, Da. Fuzzy Set Theory and Advanced Mathematical Applications. Springer US, 1995.

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5

Reghiș, Mircea. Classical and fuzzy concepts in mathematical logic and applications. CRC Press, 1998.

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6

Janssen, Jeroen, Steven Schockaert, Dirk Vermeir, and Martine de Cock. Answer Set Programming for Continuous Domains: A Fuzzy Logic Approach. Atlantis Press, 2012. http://dx.doi.org/10.2991/978-94-91216-59-6.

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7

Lowen, R. Fuzzy Set Theory: Basic Concepts, Techniques and Bibliography. Springer Netherlands, 1996.

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8

Ulrich, Höhle, Klement E. P, and Linz Seminar on Fuzzy Set Theory (14th : 1992 :, eds. Non-classical logics and their applications to fuzzy subsets: A handbook of the mathematical foundations of fuzzy set theory. Kluwr Academic Publishers, 1995.

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9

author, Malik D. S., and Clark Terry D. author, eds. Application of fuzzy logic to social choice theory. CRC Press, Taylor & Francis Group, 2015.

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10

I, Baturone, ed. Microelectronic design of fuzzy logic-based systems. CRC, 2000.

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11

Li, Shoumei. Limit theorems and applications of set-valued and fuzzy set-valued random variables. Kluwer Academic Publishers, 2002.

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12

Miyamoto, Sadaaki. Fuzzy Sets in Information Retrieval and Cluster Analysis. Springer Netherlands, 1990.

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13

Jensen, Richard. Computational intelligence and feature selection: Rough and fuzzy approaches. Wiley, 2008.

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14

1957-, Lu Jie, ed. Multi-objective group decision making: Methods, software and applications with fuzzy set techniques. Imperial College Press, 2007.

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15

1964-, Feuring Thomas, ed. Fuzzy and neural: Interactions anmd applications. Physica-Verlag, 1999.

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16

Teodorović, D. Traffic control and transport planning: A fuzzy sets and neural networks approach. Kluwer Academic Publishers, 1998.

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17

North American Fuzzy Information Processing Society. Conference. 18th International Conference of the North American Fuzzy Information Processing Society--NAFIPS: June 10-12, 199 [sic], New York, New York, U.S.A. Institute of Electrical and Electronics Engineers, 1999.

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18

Bolc, Leonard. Many-valued logics. Springer-Verlag, 1992.

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19

N, Lea Robert, Villarreal James, and United States. National Aeronautics and Space Administration. Scientific and Technical Information Program., eds. Proceedings of the Second Joint Technology Workshop on Neural Networks and Fuzzy Logic: Proceedings of a workshop sponsored by the National Aeronautics and Space Administration ... and cosponsored by Lyndon B. Johnson Space Center and the University of Houston, Clear Lake, Houston, Texas, April 10-13, 1990. National Aeronautics and Space Administration, Office of Management, Scientific and Technical Information Program, 1991.

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20

Siegfried, Gottwald, ed. Fuzzy sets, fuzzy logic, fuzzy methods with applications. J. Wiley, 1995.

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21

Hellendoorn, J. Reasoning with fuzzy logic. National Aerospace Laboratory, 1991.

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22

E, Vargas Raymond, ed. Fuzzy logic: Theory, programming, and applications. Nova Science Publishers, 2009.

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23

Bede, Barnabas. Mathematics of Fuzzy Sets and Fuzzy Logic. Springer Berlin Heidelberg, 2013.

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24

Gottwald, Siegfried. Fuzzy sets and fuzzy logic: The foundations of application--from a mathematical point of view. Teknea, 1993.

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25

Introduction to Fuzzy Set Theory and Fuzzy Logic. Viva Books Private Limited, 2015.

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26

Mohan, Chander. Introduction to Fuzzy Set Theory and Fuzzy Logic. Viva Books Private Limited, 2019.

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27

Introduction to Fuzzy Set Theory and Fuzzy Logic. Viva Books Private Limited, 2019.

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28

Walker, Carol L., Elbert A. Walker, and Hung T. Nguyen. First Course in Fuzzy Logic. Taylor & Francis Group, 2018.

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29

Walker, Carol L., Elbert A. Walker, and Hung T. Nguyen. First Course in Fuzzy Logic. Taylor & Francis Group, 2018.

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30

Walker, Elbert A., and Hung T. Nguyen. First Course in Fuzzy Logic. Taylor & Francis Group, 2005.

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31

Walker, Carol L., Elbert A. Walker, and Hung T. Nguyen. First Course in Fuzzy Logic. Taylor & Francis Group, 2018.

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32

Walker, Carol L., Elbert A. Walker, and Hung T. Nguyen. First Course in Fuzzy Logic. Taylor & Francis Group, 2018.

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33

Walker, Carol L., Elbert A. Walker, and Hung T. Nguyen. First Course in Fuzzy Logic. Taylor & Francis Group, 2018.

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34

An Introduction to Fuzzy Logic and Fuzzy Sets (Advances in Soft Computing). Physica-Verlag Heidelberg, 2002.

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35

Bělohlávek, Radim, Joseph W. Dauben, and George J. Klir. Fuzzy Logic in the Narrow Sense. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780190200015.003.0004.

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The chapter examines the various propositional and predicate many-valued logics that were studied prior to the emergence of the concept of a fuzzy set in the mid-1960s, which led to the genesis of fuzzy logic in broad and narrow senses. Early ideas regarding formal systems of fuzzy logic allowed for deduction from partially true premises to partially true consequences, as suggested first by Goguen in the 1960s and further developed by Pavelka in the 1970s, and these ideas were developed from the 1990s onward. The systematic development of fuzzy logics based on t-norms and their residua, pursued under the leadership of Hájek in the 1990s, is discussed in some detail. An overview is presented of fuzzy logics that are not truth-functional, such as probabilistic, possibilistic and modal fuzzy logic. The chapter concludes by reviewing relevant additional issues, such as issues of computational complexity for fuzzy logic or higher-order fuzzy logics.

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36

Höhle, Ulrich, and S. E. Rodabaugh. Mathematics of Fuzzy Sets: Logic, Topology, and Measure Theory (The Handbooks of Fuzzy Sets). Springer, 1998.

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37

Bělohlávek, Radim, Joseph W. Dauben, and George J. Klir. Fuzzy Logic in the Broad Sense. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780190200015.003.0003.

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The chapter begins by introducing the important and useful distinction between the research agendas of fuzzy logic in the narrow and the broad senses. The chapter deals with the latter agenda, whose ultimate goal is to employ intuitive fuzzy set theory for emulating commonsense human reasoning in natural language and other unique capabilities of human beings. Restricting to standard fuzzy sets, whose membership degrees are real numbers in the unit interval [0,1], the chapter describes how this broad agenda has become increasingly specific via the gradual development of standard fuzzy set theory and the associated fuzzy logic. An overview of currently recognized nonstandard fuzzy sets, which open various new directions in fuzzy logic, is presented in the last section of this chapter.

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38

Vermeir, Dirk, Steven Schockaert, Martine De Cock, and Jeroen Janssen. Answer Set Programming for Continuous Domains: A Fuzzy Logic Approach. Atlantis Press (Zeger Karssen), 2014.

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39

Answer Set Programming for Continuous Domains: A Fuzzy Logic Approach. Springer, 2012.

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40

Bělohlávek, Radim, Joseph W. Dauben, and George J. Klir. Prehistory, Emergence, and Evolution of Fuzzy Logic. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780190200015.003.0002.

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This chapter first identifies the rare instances throughout the long history of classical logic when the principle of bivalence was challenged and shows that they all have been rather inconsequential. It then briefly examines the early research on many-valued logics during the first half the twentieth century, and describes in some detail circumstances that led to the emergence of fuzzy set theory and fuzzy logic in the mid-1960s. This is followed by characterizing the evolving attitudes toward fuzzy logic, especially within the academic community, and by a summary of major and well-documented debates between members of the emerging fuzzy logic community and opponents of fuzzy logic. Finally, the chapter describes how the supporting infrastructure for fuzzy logic evolved during the early and rather critical stage of development of fuzzy logic.

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41

Seising, Rudolf. Fuzzification of Systems: The Genesis of Fuzzy Set Theory and Its Initial Applications - Developments up to The 1970s. Springer London, Limited, 2007.

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42

Seising, Rudolf. Fuzzification of Systems: The Genesis of Fuzzy Set Theory and Its Initial Applications - Developments up to the 1970s. Springer Berlin / Heidelberg, 2010.

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43

Belohlavek, Radim, Joseph W. Dauben, and George J. Klir. Fuzzy Logic and Mathematics. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780190200015.001.0001.

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The term “fuzzy logic” (FL) is a generic one, which stands for a broad variety of logical systems. Their common ground is the rejection of the most fundamental principle of classical logic—the principle of bivalence—according to which each declarative sentence has exactly two possible truth values—true and false. Each logical system subsumed under FL allows for additional, intermediary truth values, which are interpreted as degrees of truth. These systems are distinguished from one another by the set of truth degrees employed, its algebraic structure, truth functions chosen for logical connectives, and other properties. The book examines from the historical perspective two areas of research on fuzzy logic known as fuzzy logic in the narrow sense (FLN) and fuzzy logic in the broad sense (FLB), which have distinct research agendas. The agenda of FLN is the development of propositional, predicate, and other fuzzy logic calculi. The agenda of FLB is to emulate commonsense human reasoning in natural language and other unique capabilities of human beings. In addition to FL, the book also examines mathematics based on FL. One chapter in the book is devoted to overviewing successful applications of FL and the associated mathematics in various areas of human affairs. The principal aim of the book is to assess the significance of FL and especially its significance for mathematics. For this purpose, the notions of paradigms and paradigm shifts in science, mathematics, and other areas are introduced and employed as useful metaphors.

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44

Fuzzy Set Theory--and Its Applications. Springer Netherlands, 2001.

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45

Rajagopal, Anand. Implementation of geometric fuzzy reasoning techniques in FuzzyCLIPS. 1997.

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46

Rajagopal, Anand. Implementation of geometric fuzzy reasoning techniques in FuzzyCLIPS. 1997.

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47

Clark, Terry D., John N. Mordeson, and Davender S. Malik. Application of Fuzzy Logic to Social Choice Theory. Taylor & Francis Group, 2015.

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48

Answer Set Programming For Continuous Domains A Fuzzy Logic Approach. Atlantis Press, 2012.

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49

Reghis, Mircea S., and Eugene Roventa. Classical and Fuzzy Concepts in Mathematical Logic and Applications, Professional Version. CRC, 1998.

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50

Walker, Elbert A., and Hung T. Nguyen. A First Course in Fuzzy Logic, Third Edition. 3rd ed. Chapman & Hall/CRC, 2005.

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