Neuro-fuzzy and soft computing a computational approach to learning and machine intelligence
Neuro-Fuzzy Modeling and Soft Computing places particular emphasis on the theoretical aspects of covered methodologies, as well as empirical observations and verifications of various applications in practice. Neuro-Fuzzy Modeling and Soft Computing is oriented toward methodologies that are likely to...
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| Other Authors: | , |
| Format: | Book |
| Language: | English |
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Upper Saddle River, NJ
Prentice Hall
c1997
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| 001 | 10463 | ||
| 003 | MY-KLNDU | ||
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| 008 | 150803 1997 njua bi 000 0 eng d | ||
| 020 | |a 0132610663 | ||
| 039 | 9 | |a 201508031048 |b azraai |y 200910081523 |z VLOAD | |
| 040 | |a UPNM | ||
| 090 | |a QA 76.9.S63 |b J36 1997 | ||
| 100 | 1 | |a Jang, Jyh-Shing Roger | |
| 245 | 1 | 0 | |a Neuro-fuzzy and soft computing |b a computational approach to learning and machine intelligence |c Jyh-Shing Roger Jang, Chuen-Tsai Sun, Eiji Mizutani |
| 260 | |a Upper Saddle River, NJ |b Prentice Hall |c c1997 | ||
| 300 | |a xxvi, 614 p. |b ill. |c 24 cm | ||
| 504 | |a Includes bibliographical references and index | ||
| 505 | 0 | |a 1. Introduction to Neuro-Fuzzy and Soft Computing -- 2. Fuzzy Sets -- 3. Fuzzy Rules and Fuzzy Reasoning -- 4. Fuzzy Inference Systems -- 5. Least-Squares Methods for System Identification -- 6. Derivative-based Optimization -- 7. Derivative-Free Optimization -- 8. Adaptive Networks -- 9. Supervised Learning Neural Networks -- 10. Learning from Reinforcement -- 11. Unsupervised Learning and Other Neural Networks -- 12. ANFIS: Adaptive Neuro-Fuzzy Inference Systems -- 13. Coactive Neuro-Fuzzy Modeling: Towards Generalized ANFIS -- 14. Classification and Regression Trees -- 15. Data Clustering Algorithms -- 16. Rulebase Structure Identification -- 17. Neuro-Fuzzy Control I -- 18. Neuro-Fuzzy Control II -- 19. ANFIS Applications -- 20. Fuzzy-Filtered Neural Networks -- 21. Fuzzy Sets and Genetic Algorithms in Game Playing -- 22. Soft Computing for Color Recipe Prediction -- App. A. Hints to Selected Exercises -- App. B. List of Internet Resources. | |
| 520 | |a Neuro-Fuzzy Modeling and Soft Computing places particular emphasis on the theoretical aspects of covered methodologies, as well as empirical observations and verifications of various applications in practice. Neuro-Fuzzy Modeling and Soft Computing is oriented toward methodologies that are likely to be of practical use. It includes exercises, some of which involve MATLAB programming tasks to provide readers with hands-on programming experiences for practical problem-solving. Each chapter also includes a reference list to the research literature so that readers may pursue topics in greater depth. This book is suitable as a self-study guide by researchers who want to learn basic and advanced neuro-fuzzy and soft computing within the framework of computational intelligence. | ||
| 650 | 0 | |a Soft computing | |
| 650 | 0 | |a Neural networks (Computer science) | |
| 650 | 0 | |a Fuzzy Systems | |
| 700 | 1 | |a Sun, Chuen-Tsai | |
| 700 | 1 | |a Mizutani, Eiji | |
| 999 | |a vtls000010473 |c 10463 |d 10463 | ||