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Fuzzy Neuro Systems: An Overview

  • Detlef Nauck
Part of the Artificial Intelligence / Künstliche Intelligenz book series (CI)

Abstract

This paper gives an overview to different concepts of neural fuzzy systems. There are already several approaches to combine neural networks and fuzzy systems, to obtain adaptive systems that can use prior knowledge and that can be interpreted by means of linguistic rules as they are used e.g. in fuzzy controllers. Neural fuzzy models can be divided in two classes: Cooperative models which use neural nets and fuzzy systems separately, and hybrid models which create a new architecture using concepts from both worlds. Several of these approaches are discussed in this paper.

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References

  1. I. Aleksander and H. Morton (1990). An Introduction to Neural Computing. Chapman and Hall, London.Google Scholar
  2. C. von Altrock, B. Krause and H. Zimmermann (1992). Advanced Fuzzy Logic Control Technologies in Automotive Applications. In Proc. IEEE Int. Conf. on Fuzzy Systems 1992, pages 835–842, San Diego.CrossRefGoogle Scholar
  3. K. Asakawa and H. Takagi (1994). Neural Networks in Japan. Communications of the ACM, 37(3):106–112.CrossRefGoogle Scholar
  4. A. G. Barto, R. S. Sutton and C. W. Anderson (1983). Neuronlike Adaptive Elements that Can Solve Difficult Learning Control Problems. IEEE Trans. Systems, Man & Cybernetics, 13:834–846.Google Scholar
  5. H. R. Berenji (1992). A Reinforcement Learning-Based Architecture for Fuzzy Logic Control. Int. J. Approximate Reasoning, 6:267–292.zbMATHCrossRefGoogle Scholar
  6. H. R. Berenji and P. Khedkar (1992). Learning and Tuning Fuzzy Logic Controllers Through Reinforcements. IEEE Trans. Neural Networks, 3:724–740.CrossRefGoogle Scholar
  7. H. Bersini, J.-P. Nordvik and A. Bonarini (1993). A Simple Direct Adaptive Fuzzy Controller Derived from its Neural Equivalent. In Proc. IEEE Int. Conf. on Fuzzy Systems 1993, pages 345–350, San Francisco.CrossRefGoogle Scholar
  8. J. C. Bezdek and S. K. Pal, eds. (1992). Fuzzy Models for Pattern Recognition. IEEE Press, New York.Google Scholar
  9. D. Driankov, H. Hellendoorn and M. Reinfrank (1993). An Introduction to Fuzzy Control. Springer-Verlag, Berlin.zbMATHGoogle Scholar
  10. J.-S. R. Jang (1991). Fuzzy Modeling Using Generalized Neural Networks and Kaiman Filter Algorithm. In Proc. of the Ninth National Conf. on Artificial Intelligence (AAAI-91), pages 762–767.Google Scholar
  11. J.-S. R. Jang (1992). ANFIS: Adaptive-Network-Based Fuzzy Inference Systems. IEEE Trans. Systems, Man & Cybernetics.Google Scholar
  12. B. Kosko (1992). Neural Networks and Fuzzy Systems. A Dynamical Systems Approach to Machine Intelligence. Prentice-Hall, Englewood Cliffs.zbMATHGoogle Scholar
  13. H. Narazaki and A. L. Ralescu (1991). A Synthesis Method for Multi-Layered Neural Network using Fuzzy Sets. In IJCAI-91: Workshop on Fuzzy Logic in Artificial Intelligence, pages 54–66, Sydney.Google Scholar
  14. D. Nauck, F. Klawonn and R. Kruse (1993). Combining Neural Networks and Fuzzy Controllers. In E. P. Klement and W. Slany, eds.: Fuzzy Logic in Artificial Intelligence (FLAI93), pages 35–46, Berlin. Springer-Verlag.CrossRefGoogle Scholar
  15. D. Nauck, F. Klawonn and K. Rudolf (1994). Neuronale Netze und Fuzzy-Systeme (Neural Networks and Fuzzy Systems, in German). Vieweg-Verlag, Braunschweig.Google Scholar
  16. D. Nauck and R. Kruse (1992). Interpreting Changes in the Fuzzy Sets of a Self-Adaptive Neural Fuzzy Controller. In Proc. Second Int. Workshop on Industrial Applications of Fuzzy Control and Intelligent Systems (IFIS’92), pages 146–152, College Station, Texas.Google Scholar
  17. D. Nauck and R. Kruse (1993). A Fuzzy Neural Network Learning Fuzzy Control Rules and Membership Functions by Fuzzy Error Backpropagation. In Proc. IEEE Int. Conf. on Neural Networks 1993, pages 1022–1027, San Francisco.CrossRefGoogle Scholar
  18. D. Nauck and R. Kruse (1994). NEFCON-I: An X-Window based Simulator for Neural Fuzzy Controllers. In Proc. IEEE Int. Conf. Neural Networks 1994 at IEEE WCCI’94, Orlando. To be published.Google Scholar
  19. H. Nomura, I. Hayashi and N. Wakami (1992). A Learning Method of Fuzzy Inference Rules by Descent Method. In Proc. IEEE Int. Conf. on Fuzzy Systems 1992, pages 203–210, San Diego.CrossRefGoogle Scholar
  20. A. Nowé and R. Vepa (1993). A Reinforcement Learning Algorithm based on ‘Safety’. In E. P. Klement and W. Slany, eds.: Fuzzy Logic in Artificial Intelligence (FLAI93), pages 47–58, Berlin. Springer-Verlag.CrossRefGoogle Scholar
  21. W. Pedrycz and W. C. Card (1992). Linguistic Interpretation of Self-Organizing Maps. In Proc. IEEE Int. Conf. on Fuzzy Systems 1992, pages 371–378, San Diego.CrossRefGoogle Scholar
  22. T. J. Procyk and E. H. Mamdani (1979). A Linguistic Self-Organizing Process Controller. Automatica, 15:15–30.zbMATHCrossRefGoogle Scholar
  23. W. Z. Qiao, W. P. Zhuang, T. H. Heng and S. S. Shan (1992). A Rule Self-Regulating Fuzzy Controller. Fuzzy Sets and Systems, 47:13–21.MathSciNetCrossRefGoogle Scholar
  24. R. Rojas (1993). Theorie der Neuronalen Netze: Eine systematische Einführung. Springer-Verlag, Berlin.CrossRefGoogle Scholar
  25. S. Shao (1988). Fuzzy Self-Organizing Controller and its Application for Dynamic Processes. Fuzzy Sets and Systems, 26:151–164.MathSciNetCrossRefGoogle Scholar
  26. P. Simpson (1992a). Fuzzy Min-Max Neural Networks — Part 1: Classification. IEEE Trans. Neural Networks, 3:776–786.CrossRefGoogle Scholar
  27. P. Simpson (1992b). Fuzzy Min-Max Neural Networks — Part 2: Clustering. IEEE Trans. Fuzzy Systems, 1:32–45.CrossRefGoogle Scholar
  28. S. M. Sulzberger, N. N. Tschichold-Gürman and S. J. Vestli (1993). FUN: Optimization of Fuzzy Rule Based Systems using Neural Networks. In Proc. IEEE Int. Conf. on Neural Networks 1993, pages 312–316, San Francisco.CrossRefGoogle Scholar
  29. H. Takagi and I. Hayashi (1991). NN-Driven Fuzzy Reasoning. Int. J. Approximate Reasoning, 5:191–212.zbMATHCrossRefGoogle Scholar
  30. D. A. White and D. A. Sofge, eds. (1992). Handbook of Intelligent Control. Neural, Fuzzy, and Adaptive Approaches. Van Nostrand Reinhold, New York.Google Scholar
  31. T. Yamaguchi, K. Goto, T. Takagi, K. Doya and T. Mita (1992). Intelligent Control of a Flying Vehicle using Fuzzy Associative Memory System. In Proc. IEEE Int. Conf. on Fuzzy Systems 1992, pages 1139–1149.CrossRefGoogle Scholar

Copyright information

© Friedr. Vieweg & Sohn Verlagsgesellschaft mbH, Braunschweig/Wiesbaden 1994

Authors and Affiliations

  • Detlef Nauck

There are no affiliations available

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