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Genetic Algorithms and Fuzzy Systems

  • Larry R. Medsker

Abstract

The integration of genetic algorithms with fuzzy systems is newer and less well explored than the combining of genetic algorithms or fuzzy logic with neural networks. The pioneering work in this area starts around 1989 and much of the initiative is due to Charles Karr. The most promising application area for the short term is the use of genetic algorithms to improve fuzzy logic controllers. This is an emerging field in which important work has proven the usefulness in some areas, but further studies will explore additional creative ways of integration.

Keywords

Genetic Algorithm Membership Function Fuzzy Logic Fuzzy System Fuzzy Rule 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References for Further Reading

  1. Ankenbrandt, C. A., Buckles, B. P., and Petry, F. E. (1990), “Scene recognition using genetic algorithms with semantic nets,” Pattern Recognition Letters, vol 11, pp. 285–293.zbMATHCrossRefGoogle Scholar
  2. Fukuda, T., and Shibata, T. (1994), “Fuzzy-neuro-GA based intelligent robotics,” in [Zurada, Marks, and Robinson, 1994] at pp. 352–363.Google Scholar
  3. Goldberg, D. E. (1989), Genetic Algorithms in Search, Optimization, and Machine Learning, Addison-Wesley, Reading, MA.zbMATHGoogle Scholar
  4. Ishigami, H., Hasegawa, T., Fukuda, T., and Shibata, T. (1994) “Automatic generation of hierarchical structure of fuzzy inference by genetic algorithm,” Proceedings of the IEEE International Conference on Neural Networks, vol III, IEEE World Congress on Computational Intelligence, Orlando, FL, pp. 1566–1570.Google Scholar
  5. Karr, C. (1991), “Genetic algorithms for fuzzy controllers,” AI Expert, vol 6, no. 2, pp. 26–33.Google Scholar
  6. Karr, C. (1991), “Applying genetics to fuzzy logic,” AI Expert, vol 6, no. 3, pp. 38–43.MathSciNetGoogle Scholar
  7. Schaffer, J. D. (1994), “Combinations of genetic algorithms with neural networks or fuzzy systems,” in [Zurada, Marks, and Robinson, 1994] at pp. 371–382.Google Scholar
  8. Ward, T. L., and Ralston, P. A. S. (eds.) (1995), Intelligent Control of Engineering Machines and Processes, Dekker, New York.Google Scholar
  9. Zeng, S., and He, Y. (1994), “Learning and tuning fuzzy logic controllers through genetic algorithms,” Proceedings of the IEEE International Conference on Neural Networks, vol III, IEEE World Congress on Computational Intelligence, Orlando, FL, pp. 1632–1637.Google Scholar
  10. Zimmerman, H. J. (1994), “Hybrid approaches for fuzzy data analysis and configuration using genetic algorithms and evolutionary methods,” in [Zurada, Marks, and Robinson, 1994] at pp. 364–370.Google Scholar

The following conference proceedings are good sources of information on work with genetic algorithms and fuzzy logic

  1. ICGA’93 (1993), Proceedings of the Fifth International Conference on Genetic Algorithms, Forrest, S. (ed), Morgan Kaufmann.Google Scholar
  2. IEEE FUZZ’92 (1992), Proceedings of the IEEE International Conference on Fuzzy Systems, San Diego, March 8-12.Google Scholar
  3. IEEE FUZZY (1993), Proceedings of the IEEE 2nd International Fuzzy Systems Conference, San Francisco, March 28-April 1.Google Scholar
  4. IEEE FUZZ’94 (1994), Proceedings of the IEEE International Conference on Fuzzy Systems, IEEE World Congress on Computational Intelligence, Orlando, FL, June 28-July 2.Google Scholar
  5. IEEE ICEC94 (1994), Proceedings of the IEEE International Conference on Evolutionary Computation, IEEE World Congress on Computational Intelligence, Orlando, FL, June 28-July 2.Google Scholar
  6. IEEE ICNN’93 (1993), Proceedings of the IEEE International Conference on Neural Networks, San Francisco, March 28-April 1.Google Scholar
  7. IEEE ICNN’94 (1994), Proceedings of the IEEE International Conference on Neural Networks, IEEE World Congress on Computational Intelligence, Orlando, FL, June 28-July 2.Google Scholar
  8. IEEE CGANN (1992), Proceedings of the Workshop on Combinations of Genetic Algorithms and Neural Networks, Baltimore, MD, June 7-11Google Scholar
  9. IJCNN’92 (1992), Proceedings of the International Joint Conference on Neural Networks, Baltimore, MD, June 7-11.Google Scholar
  10. WCNN’93 (1993), Proceedings of the World Congress on Neural Networks, Portland, OR, July 11-15.Google Scholar
  11. WCNN’94 (1994), Proceedings of the World Congress on Neural Networks, San Diego, June 5-9.Google Scholar

Additional conference proceedings that have a few references relevant to this chapter

  1. BCCMA (1993), Proceedings of the Fifth International Workshop of the Bellman Continuum, Computers & Mathematics with Applications, vol 27, no. 9-10, Waikoloa, HI, January 11-12, 1993.Google Scholar
  2. CAI’93 (1993) Proceedings of the Third Conference on Artificial Intelligence, Budapest, Hungary, April 6-8.Google Scholar
  3. ICEC’94, Proceedings of the First IEEE Conference on Evolutionary Computation, IEEE World Congress on Computational Intelligence, Orlando, FL, June 27-29.Google Scholar
  4. IFIP TC5/WG5.7 (1994), IFIP Transactions B (Applications in Technology), vol B-15, International Workshop on Knowledge-Based Reactive Scheduling, Athens, Greece, October 1.Google Scholar
  5. TAF94 (1994), Proceedings of the Sixth International Conference on Tools with Artificial Intelligence, New Orleans, 6-9 Nov. 6-9.Google Scholar
  6. WNN’92 (1992), Proceedings of the Third Workshop on Neural Networks: Academic/Industrial/NASA/Defense, Auburn, AL, and Houston, TX, February, 10-12 and November 4-6.Google Scholar
  7. WWW’94 (1994), Proceedings of the IEEE/Nagoya University World Wisemen/Women Workshop on Fuzzy Logic and Neural Networks/Genetic Algorithms, Nagoya, Japan, August 9-10.Google Scholar

Copyright information

© Springer Science+Business Media New York 1995

Authors and Affiliations

  • Larry R. Medsker
    • 1
  1. 1.Department of Computer Science and Information SystemsThe American UniversityUSA

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