| Titre : | Neuro-Fuzzy architectures and hybrid learning : with 102 figures and 3 tables | | Type de document : | texte imprimé | | Auteurs : | Danuta Rutkowska, Auteur | | Editeur : | Heidelberg : Physiqua-Verlag | | Année de publication : | 2002 | | Collection : | Studies in Fuzziness and Soft Computing | | Importance : | 288 p. | | Présentation : | couv. ill. en coul., ill. | | Format : | 23 cm. | | ISBN/ISSN/EAN : | 978-3-7908-1438-5 | | Langues : | Anglais (eng) | | Catégories : | INFORMATIQUE
| | Index. décimale : | 08-06 Algorithme | | Résumé : | The main idea of this book is to present novel connectionist architectures of neuro-fuzzy systems, especially those based on the logical approach to fuzzy inference. In addition, hybrid learning methods are proposed to train the networks. The neuro-fuzzy architectures plus hybrid learning are considered as intelligent systems within the framework of computational and artificial intelligence. The book also provides an overview of fuzzy sets and systems, neural networks, learning algorithms (including genetic algorithms and clustering methods), as well as expert systems and perception-based systems which incorporates computing with words. | | Note de contenu : | Table of contents
1. Introduction
2. Description of Fuzzy Inference Systems
3. Neural Networks and Neuro-Fuzzy Systems
4. Neuro-Fuzzy Architectures Based on the Mamdani Approach
5. Neuro-Fuzzy Architectures Based on the Logical Approach
6. Hybrid Learning Methods
7. Intelligent Systems
8. Summary |
Neuro-Fuzzy architectures and hybrid learning : with 102 figures and 3 tables [texte imprimé] / Danuta Rutkowska, Auteur . - Heidelberg : Physiqua-Verlag, 2002 . - 288 p. : couv. ill. en coul., ill. ; 23 cm.. - ( Studies in Fuzziness and Soft Computing) . ISBN : 978-3-7908-1438-5 Langues : Anglais ( eng) | Catégories : | INFORMATIQUE
| | Index. décimale : | 08-06 Algorithme | | Résumé : | The main idea of this book is to present novel connectionist architectures of neuro-fuzzy systems, especially those based on the logical approach to fuzzy inference. In addition, hybrid learning methods are proposed to train the networks. The neuro-fuzzy architectures plus hybrid learning are considered as intelligent systems within the framework of computational and artificial intelligence. The book also provides an overview of fuzzy sets and systems, neural networks, learning algorithms (including genetic algorithms and clustering methods), as well as expert systems and perception-based systems which incorporates computing with words. | | Note de contenu : | Table of contents
1. Introduction
2. Description of Fuzzy Inference Systems
3. Neural Networks and Neuro-Fuzzy Systems
4. Neuro-Fuzzy Architectures Based on the Mamdani Approach
5. Neuro-Fuzzy Architectures Based on the Logical Approach
6. Hybrid Learning Methods
7. Intelligent Systems
8. Summary |
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Neuro-Fuzzy architectures and hybrid learning / Danuta Rutkowska
