Fuzzy Logic, Neural Networks, and Evolutionary Computation

1. Front Matter

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2. The design of hybrid fuzzy/evolutionary multiobjective optimization algorithms

   • Michael A. Lee, Henrik Esbensen, Laurent Lemaitre

   Pages 1-20

3. Structure identification of acquired knowledge in fuzzy inference by genetic algorithms

   • Shohachiro Nakanishi, Akihiro Ohtake, Ronald R. Yager, Shinobu Ohtani, Hiroaki Kikuchi

   Pages 21-34

4. A fuzzy classifier system that generates linguistic rules for pattern classification problems

   • Hisao Ishibuchi, Tomoharu Nakashima, Tadahiko Murata

   Pages 35-54

5. Numerical coding and unfair average crossover in GA for fuzzy rule extraction in dynamic environments

   • Tatsuya Nomura, Tsutomu Miyoshi

   Pages 55-72

6. Acquisition of fuzzy rules from DNA coding method

   • Tomohiro Yoshikawa, Takeshi Furuhashi, Yoshiki Uchikawa

   Pages 73-88

7. Experimental study on acquisition of optimal action for autonomous mobile robot to avoid moving multiobstacles

   • Takeshi Aoki, Toshiaki Oka, Soichiro Hayakawa, Tatsuya Suzuki, Shigeru Okuma

   Pages 89-103

8. New approaches on structure identification of fuzzy models: Case study in an electro-mechanical system

   • P. J. Costa Branco, N. Lori, J. A. Dente

   Pages 104-143

9. A generic fuzzy neuron and its application to motion estimation

   • Abbas Z. Kouzani, Abdesselam Bouzerdoum

   Pages 144-171

10. Fizzy-Fuzzy inferencing

    • Andrzej Buller

    Pages 172-187

11. Multi-layer perceptron design using Delaunay triangulations

    • Elena Pérez-Miñana, Peter Ross, John Hallam

    Pages 188-197

12. A genetic algorithm for planning coal purchase of a real electric power plant

    • Masahiro Inuiguchi, Tadahiro Miyake, Masatoshi Sakawa, Isao Shiromaru

    Pages 198-214

13. “CAM-Brain∝ ATR's billion neuron artificial brain project a three year progress report

    • Hugo de Garis

    Pages 215-243

14. Back Matter

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This book includes a selection of twelve carefully revised papers chosen from the papers accepted for presentation at the 4th IEEE/Nagoya-University World Wisepersons Workshop held in Nagoya in November 1995.
The combining of the technologies of fuzzy logic, neural networks, and evolutionary computation is expected to open up a new paradigm of machine learning for the realization of human-like information generating systems. The excellent papers presented are organized in sections on fuzzy and evolutionary computation, fuzzy and learning automata, fuzzy and neural networks, genetic algorithms, and CAM-brain.

• Evolutionary Computing
• Fuzzy-Logik
• Genetische Algorithmen
• Lernende Automaten
• Neural Networks
• algorithms
• fuzzy logic
• learning automata
• machine learning

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