Advances in Fuzzy Logic, Neural Networks, and Genetic Algorithms : Ieee/Nagoya-University World Wisepersons Workshop Nagoya, Japan, August 9-10, 1994 : Selected Papers. Questo articolo non è disponibile.
Lingua: inglese
Editore: Springer, 1995
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Codice articolo 5905650
- Titolo
- Advances in Fuzzy Logic, Neural Networks, and Genetic Algorithms : Ieee/Nagoya-University World Wisepersons Workshop Nagoya, Japan, August 9-10, 1994 : Selected Papers
- Autore
- Furuhashi, Takeshi (EDT)
- Editore
- Springer
- Anno di pubblicazione
- 1995
- Condizione
- As New
- Rilegatura
- Brossura
- Lingua
- inglese
- ISBN 10
- 3540606076
- ISBN 13
- 9783540606079
This book presents 14 rigorously reviewed revised papers selected from more than 50 submissions for the 1994 IEEE/ Nagoya-University World Wisepersons Workshop, WWW'94, held in August 1994 in Nagoya, Japan. The combination of approaches based on fuzzy logic, neural networks and genetic algorithms are expected to open a new paradigm of machine learning for the realization of human-like information processing systems. The first six papers in this volume are devoted to the combination of fuzzy logic and neural networks; four papers are on how to combine fuzzy logic and genetic algorithms. Four papers investigate challenging applications of fuzzy systems and of fuzzy-genetic algorithms.
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Contenuti
Fuzzy associative memory system and its application to multi-modal interface.- Hybrid connectionist fuzzy systems for speech recognition and the use of connectionist production systems.- Fuzzy gaussian potential neural networks using a functional reasoning.- Recurrent fuzzy logic using neural network.- Information aggregating networks based on extended Sugeno's fuzzy integral.- A neuro-fuzzy architecture for high performance classification.- Investigation of stability and robustness of a fuzzy traction control system.- Knowledge-based rules for control of the sake (Ginjoshu) making process and their application in fuzzy control.- A framework for studying the effects of dynamic crossover, mutation, and population sizing in genetic algorithms.- Unsupervised/supervised learning for RBF-fuzzy system.- Genetic algorithms for the development of fuzzy controllers for mobile robots.- A new approach to genetic based machine learning and an efficient finding of fuzzy rules.- A neuro-money recognition using optimized masks by GA.- Genetic-fuzzy systems for financial decision making.
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