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Books on the topic 'Genetic algorithms and fuzzy logic'

Author: Grafiati

Published: 4 June 2021

Last updated: 9 February 2022

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1

Genetic algorithms and fuzzy multiobjective optimization. Boston: Kluwer Academic Publishers, 2002.

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2

Furuhashi, Takeshi, ed. Advances in Fuzzy Logic, Neural Networks and Genetic Algorithms. Berlin, Heidelberg: Springer Berlin Heidelberg, 1995. http://dx.doi.org/10.1007/3-540-60607-6.

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3

Ruan, Da. Intelligent Hybrid Systems: Fuzzy Logic, Neural Networks, and Genetic Algorithms. Boston, MA: Springer US, 1997.

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4

Fuzzy modeling and genetic algorithms for data mining and exploration. San Francisco, CA: Elsevier/Morgan Kaufmann, 2004.

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5

Adeli, Hojjat. Cost optimization of structures: Fuzzy logic, genetic algorithms, and parallel computing. Chichester, England: Wiley, 2006.

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6

McClintock, Shaunna. Soft computing: A fuzzy logic controlled genetic algorithm environment. [S.l: The Author], 1999.

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7

Karr, C. L. An adaptive system for process control. [Washington, D.C.?]: U.S. Dept. of the Interior, Bureau of Mines, 1995.

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8

Karr, C. L. An adaptive system for process control. [Washington, D.C.?]: U.S. Dept. of the Interior, Bureau of Mines, 1995.

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9

Soft computing in water resources engineering: Artificial neural networks, fuzzy logic and genetic algorithms. Southampton: WIT Press, 2012.

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10

IEEE/Nagoya University World Wisepersons Workshop (1994 Nagoya-shi, Japan). Advances in fuzzy logic, neural networks, and genetic algorithms: IEEE/Nagoya University World Wisepersons Workshop, Nagoya, Japan, August 9-10, 1994 : selected papers. Berlin: Springer, 1995.

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11

IEEE/Nagoya-University World Wisepersons Workshop on Fuzzy Logic and Neural Networks/Evolutionary Computation (1995 Nagoya, Japan). Proceedings of the 1995 IEEE/Nagoya-University World Wisepersons Workshop (WWW '95) on Fuzzy Logic and Neural Networks/Evolutionary Computation: November 14 and 15, 1995, Rubrum Ohzan, Nagoya, Japan. Nagoya, Japan: Nagoya University, 1995.

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12

Inc, NetLibrary, ed. The nonlinear workbook: Chaos, fractals, cellular automata, neural networks, genetic algorithms, fuzzy logic : with C++, Java, SymbolicC++ and Reduce programs. Singapore: World Scientific, 2001.

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13

Chaos theory in the financial markets: Applying fractals, fuzzy logic, genetic algorithms, swarm simulation & the Monte Carlo method to manage market chaos & volatility. Chicago, Ill: Probus Pub. Co., 1994.

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14

The nonlinear workbook: Chaos, fractals, cellular automata, genetic algorithms, gene expression programming, support vector machine, wavelets, hidden Markov models, fuzzy logic with C++, Java and symbolic C++ programs. 6th ed. Hackensack, New Jersey: World Scientific, 2015.

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15

Tucci, Mario, and Marco Garetti, eds. Proceedings of the third International Workshop of the IFIP WG5.7. Florence: Firenze University Press, 2002. http://dx.doi.org/10.36253/88-8453-042-3.

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Abstract:

Contents of the papers presented at the international workshop deal with the wide variety of new and computer-based techniques for production planning and control that has become available to the scientific and industrial world in the past few years: formal modeling techniques, artificial neural networks, autonomous agent theory, genetic algorithms, chaos theory, fuzzy logic, simulated annealing, tabu search, simulation and so on. The approach, while being scientifically rigorous, is focused on the applicability to industrial environment.

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16

The nonlinear workbook: Chaos, fractals, cellular automata, neural networks, genetic algorithms, gene expression programming, support vector machine, wavelets, hidden Markov models, Fuzzy logic with C++, Java and SymbolicC++ programs. 5th ed. New Jersey: World Scientific, 2011.

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17

The nonlinear workbook: Chaos, fractals, cellular automata, neural networks, genetic algorithms, gene expression programming, support vector machine, wavelets, hidden Markov models, Fuzzy logic with C++, Java and SymbolicC++ programs. 3rd ed. Hackensack, NJ: World Scientific, 2005.

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18

The nonlinear workbook: Chaos, fractals, cellular automata, neural networks, genetic algorithms, gene expression programming, support vector machine, wavelets, hidden Markov models, Fuzzy logic with C++, Java and SymbolicC++ programs. 5th ed. New Jersey: World Scientific, 2011.

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19

The nonlinear workbook: Chaos, fractals, cellular automata, neural networks, genetic algorithms, gene expression programming, support vector machine, wavelets, hidden Markov models, Fuzzy logic with C++, Java and SymbolicC++ programs. 4th ed. New Jersey: World Scientific, 2008.

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20

Sakawa, Masatoshi. Genetic Algorithms and Fuzzy Multiobjective Optimization. Boston, MA: Springer US, 2002. http://dx.doi.org/10.1007/978-1-4615-1519-7.

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21

International Conference on Knowledge-Based Intelligent Electronic Systems (2nd 1998 Adelaide, South Australia). 1998 second International Conference on Knowledge-Based Intelligent Electronic Systems: Proceedings : KES '98 : Adelaide, South Australia, 21-23 April, 1998. Edited by Jain L. C, Jain R. K, and Institute of Electrical and Electronics Engineers. Piscataway, New Jersey: IEEE, 1998.

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22

International Conference on Knowledge-Based Intelligent Information Engineering Systems (3rd 1999 Adelaide, South Australia). 1999 third International Conference on Knowledge-Based Intelligent Information Engineering Systems: Proceedings : KES '99 : Adelaide, South Australia, 31 August-1 September 1999. Edited by Jain L. C, Institute of Electrical and Electronics Engineers., and International Conference on Knowledge-Based Intelligent Electronic Systems. Piscataway, New Jersey: IEEE, 1999.

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23

Verbruggen, H. B. Fuzzy Algorithms for Control. Dordrecht: Springer Netherlands, 1999.

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24

Suryana, Yaya. Genetic design of fuzzy logic controllers. Salford: University of Salford, 1995.

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25

Islam, Rafiqul. Genetic algorithms, fuzzy systems, and website classification. Hauppauge, N.Y: Nova Science Publishers, 2011.

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26

Identeki arugorizumu no kōzō kōgaku e no ōyō / Furuta Hitoshi, Sugimoto Hiroyuki cho. Tōkyō: Morikita Shuppan Kabushiki Kaisha, 2011.

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27

Identeki arugorizumu no kōzō kōgaku e no ōyō / Furuta Hitoshi, Sugimoto Hiroyuki cho. Tōkyō: Morikita Shuppan Kabushiki Kaisha, 2011.

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28

Brox, Piedad, Iluminada Baturone, and Santiago Sánchez-Solano. Fuzzy Logic-Based Algorithms for Video De-Interlacing. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-10695-8.

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29

Adeli, Hojjat. Machine learning: Neural networks, genetic algorithms, and fuzzy systems. New York: Wiley, 1995.

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30

R, Aliev R., ed. Soft computing and its applications. Singapore: World Scientific Press, 2001.

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31

Pawar, Prashant M. Structural health monitoring using genetic fuzzy systems. London: Springer, 2011.

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32

Geyer-Schulz, Andreas. Fuzzy rule-based expert systems and genetic machine learning. Heidelberg: Physica-Verlag, 1995.

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33

Fuzzy rule-based expert systems and genetic machine learning. 2nd ed. Heidelberg: Physica-Verlag, 1997.

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34

Castillo, Oscar, and Patricia Melin, eds. Fuzzy Logic Hybrid Extensions of Neural and Optimization Algorithms: Theory and Applications. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-68776-2.

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35

Castillo, Oscar, Patricia Melin, and Janusz Kacprzyk, eds. Fuzzy Logic Augmentation of Neural and Optimization Algorithms: Theoretical Aspects and Real Applications. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-71008-2.

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36

Olivas, Frumen, Fevrier Valdez, Oscar Castillo, and Patricia Melin. Dynamic Parameter Adaptation for Meta-Heuristic Optimization Algorithms Through Type-2 Fuzzy Logic. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-70851-5.

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37

Vas, Peter. Artificial-intelligence-based electrical machines and drives: Application of fuzzy, neural, fuzzy-neural, and genetic-algorithm-based techniques. Oxford: Oxford University Press, 1999.

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38

Lodwick, Weldon A., and Janusz Kacprzyk. Fuzzy optimization: Recent advances and applications. Berlin: Springer, 2010.

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39

Intelligent systems and financial forecasting. London: Springer, 1997.

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40

Castillo, Oscar, Patricia Melin, and Janusz Kacprzyk, eds. Intuitionistic and Type-2 Fuzzy Logic Enhancements in Neural and Optimization Algorithms: Theory and Applications. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-35445-9.

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41

Taylor, Cynthia. A programmer's guide to the fuzzy logic ramp metering algorithm: Software design, integration, testing, and evaluation. [Olympia, Wash.]: Washington State Dept. of Transportation, 2000.

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42

Taylor, Cynthia. Algorithm design, user interface, and optimization procedure for a fuzzy logic ramp metering algorithm: A training manual for freeway operations engineers. [Olympia, Wash.]: Washington State Dept. of Transportation, 2000.

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43

Sanchez, Elie, Takanori Shibata, and Lotfi A. Zadeh. Genetic Algorithms and Fuzzy Logic Systems. WORLD SCIENTIFIC, 1997. http://dx.doi.org/10.1142/2896.

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44

Rajashekaran, S., and G. A. Vijayalksmi. Neural Networks, Fuzzy Logic and Genetic Algorithms. Prentice-Hall of India Pvt.Ltd, 2004.

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45

1944-, Sanchez Elie, Shibata Takanori 1967-, and Zadeh Lotfi Asker, eds. Genetic algorithms and fuzzy logic systems: Soft computing perspectives. Singapore: World Scientific Pub., 1997.

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46

(Editor), Elie Sanchez, Takanori Shibata (Editor), and Lotfi Asker Zadeh (Editor), eds. Genetic Algorithms and Fuzzy Logic Systems: Soft Computing Perspectives (Advances in Fuzzy Systems - Applications and Theory, Vol 7). World Scientific Pub Co Inc, 1997.

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47

Da, Ruan, ed. Intelligent hybrid systems: Fuzzy logic, neural networks, and genetic algorithms. Boston: Kluwer Academic Publishers, 1997.

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48

Ruan, Da. Intelligent Hybrid Systems: Fuzzy Logic, Neural Networks, and Genetic Algorithms. Springer, 2011.

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49

Ruan, Da. Intelligent Hybrid Systems: Fuzzy Logic, Neural Networks, and Genetic Algorithms. Springer, 1997.

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50

Adeli, Hojjat, and Kamal C. Sarma. Cost Optimization of Structures: Fuzzy Logic, Genetic Algorithms, and Parallel Computing. Wiley & Sons, Incorporated, John, 2006.

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