Complexity Management in Fuzzy Systems | A Rule Base Compression Approach

Alexander Gegov

ISBN 10: 3540388834 / ISBN 13: 9783540388838

Editore: Springer-Verlag GmbH, 2007

Riguardo questo articolo

Complexity Management in Fuzzy Systems | A Rule Base Compression Approach | Alexander Gegov | Buch | xv | Englisch | 2007 | Springer-Verlag GmbH | EAN 9783540388838 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu Print on Demand.

Codice articolo 112012216

Dati bibliografici

• Titolo: Complexity Management in Fuzzy Systems | A Rule Base Compression Approach
• Editore: Springer-Verlag GmbH
• Data di pubblicazione: 2007
• Lingua: Inglese
• ISBN 10: 3540388834
• ISBN 13: 9783540388838
• Rilegatura: Buch
• Condizione: Neu
• Dimensioni: 241 L x 160 A x 26 P (millimetri) 241 millimetri di larghezza per 160 millimetri di altezza per 26 millimetri di profondità
• Peso: 711 grammi
• Cataloghi dei venditori:
  • Bücher

Descrizione articolo

Riassunto

This book presents a systematic study on the inherent complexity in fuzzy systems, resulting from the large number and the poor transparency of the fuzzy rules. The study uses a novel approach for complexity management, aimed at compressing the fuzzy rule base by removing the redundancy while preserving the solution. The compression is based on formal methods for presentation, manipulation, transformation and simplification of fuzzy rule bases.

Dalla quarta di copertina

This book presents a systematic study on the inherent complexity in fuzzy systems, resulting from the large number and the poor transparency of the fuzzy rules. The study uses a novel approach for complexity management, aimed at compressing the fuzzy rule base by removing the redundancy while preserving the solution. The compression is based on formal methods for presentation, manipulation, transformation and simplification of fuzzy rule bases, which are illustrated by algorithms as well as results from numerous examples and two case studies. The results are directly applicable or easily extendable to a wide class of fuzzy systems and detailed benchmarks for expanding these systems to new areas such as fuzzy networks and fuzzy multi-agent systems are introduced. The intended readers are people from both academia and industry, who would be interested in building and implementing advanced fuzzy systems.