| Titre : |
Fuzzy expert systems and fuzzy reasoning |
| Type de document : |
texte imprimé |
| Auteurs : |
Silier,William, Auteur ; James J. Buckley, Auteur |
| Editeur : |
New York : John Wiley & Sons |
| Année de publication : |
2001 |
| Importance : |
XVI-405 p. |
| Présentation : |
ill. |
| Format : |
24 cm |
| ISBN/ISSN/EAN : |
978-0-471-38859-3 |
| Note générale : |
Bibliogr. 399-402. Index |
| Langues : |
Français (fre) |
| Mots-clés : |
Informatique Ordinateur
Systeme expert
Fuzzy expert -- Fuzzy reasoning |
| Index. décimale : |
681.3.02 Conception,construction et structures des systèmes machines et éléments de traitement de données.(Conception des systèmes) |
| Résumé : |
Fuzzy sets were for a long time not accepted by the AI community. Now they have become highly evolved and their techniques are well established. This book will teach the reader how to construct a fuzzy expert system to solve real-world problems. After a general discussion of expert systems, the basic fuzzy math required is presented first, requiring little more math background than high-school algebra. This book will fill a void in the market because although there are many books on expert systems, none devote more than a few pages to the notion of fuzzy sets and their applications in this domain. Therefore their use in this book is timely and should be well received.
The book is designed as a text and has ample problems with solutions, a solutions manual and an accompanying program on our ftp site. Coverage is accessible to practitioners and academic readers alike. |
| Note de contenu : |
Sommaire:
1 Introduction.
2 Rule-Based Systems: Overview.
3 Fuzzy Logic, Fuzzy Sets, and Fuzzy Numbers: I.
4 Fuzzy Logic, Fuzzy Sets, and Fuzzy Numbers: II.
5 Combining Uncertainties.
6 Inference in an Expert System I.
7 Inference in a Fuzzy Expert System II: Modification of Data and Truth Values.
8 Resolving Contradictions: Possibility and Necessity.
9 Expert System Shells and the Integrated Development Environment (IDE).
10 Simple Example Programs.
11 Running and Debugging Fuzzy Expert Systems I: Parallel Programs.
12 Running and Debugging Expert Systems II: Sequential Rule-Firing.
13 Solving “What?” Problems when the Answer is Expressed in Words.
14 Programs that Can Learn from Experience.
15 Running On-Line in Real-Time. |
Fuzzy expert systems and fuzzy reasoning [texte imprimé] / Silier,William, Auteur ; James J. Buckley, Auteur . - New York : John Wiley & Sons, 2001 . - XVI-405 p. : ill. ; 24 cm. ISBN : 978-0-471-38859-3 Bibliogr. 399-402. Index Langues : Français ( fre)
| Mots-clés : |
Informatique Ordinateur
Systeme expert
Fuzzy expert -- Fuzzy reasoning |
| Index. décimale : |
681.3.02 Conception,construction et structures des systèmes machines et éléments de traitement de données.(Conception des systèmes) |
| Résumé : |
Fuzzy sets were for a long time not accepted by the AI community. Now they have become highly evolved and their techniques are well established. This book will teach the reader how to construct a fuzzy expert system to solve real-world problems. After a general discussion of expert systems, the basic fuzzy math required is presented first, requiring little more math background than high-school algebra. This book will fill a void in the market because although there are many books on expert systems, none devote more than a few pages to the notion of fuzzy sets and their applications in this domain. Therefore their use in this book is timely and should be well received.
The book is designed as a text and has ample problems with solutions, a solutions manual and an accompanying program on our ftp site. Coverage is accessible to practitioners and academic readers alike. |
| Note de contenu : |
Sommaire:
1 Introduction.
2 Rule-Based Systems: Overview.
3 Fuzzy Logic, Fuzzy Sets, and Fuzzy Numbers: I.
4 Fuzzy Logic, Fuzzy Sets, and Fuzzy Numbers: II.
5 Combining Uncertainties.
6 Inference in an Expert System I.
7 Inference in a Fuzzy Expert System II: Modification of Data and Truth Values.
8 Resolving Contradictions: Possibility and Necessity.
9 Expert System Shells and the Integrated Development Environment (IDE).
10 Simple Example Programs.
11 Running and Debugging Fuzzy Expert Systems I: Parallel Programs.
12 Running and Debugging Expert Systems II: Sequential Rule-Firing.
13 Solving “What?” Problems when the Answer is Expressed in Words.
14 Programs that Can Learn from Experience.
15 Running On-Line in Real-Time. |
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