Computational Intelligence - Rutkowski, Leszek
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  • Broschiertes Buch

This quite simply superb book focuses on various techniques of computational intelligence, both single ones and those which form hybrid methods. These techniques are today commonly applied to issues of artificial intelligence. The book presents methods of knowledge representation using different techniques, namely the rough sets, type-1 fuzzy sets and type-2 fuzzy sets. Next up, various neural network architectures are presented and their learning algorithms are derived. Then, the family of evolutionary algorithms is discussed, including connections between these techniques and neural networks…mehr

Produktbeschreibung
This quite simply superb book focuses on various techniques of computational intelligence, both single ones and those which form hybrid methods. These techniques are today commonly applied to issues of artificial intelligence. The book presents methods of knowledge representation using different techniques, namely the rough sets, type-1 fuzzy sets and type-2 fuzzy sets. Next up, various neural network architectures are presented and their learning algorithms are derived. Then, the family of evolutionary algorithms is discussed, including connections between these techniques and neural networks and fuzzy systems. Finally, various methods of data partitioning and algorithms of automatic data clustering are given and new neuro-fuzzy architectures are studied and compared.

  • Produktdetails
  • Verlag: Springer / Springer, Berlin
  • Artikelnr. des Verlages: 978-3-642-09515-3
  • Softcover reprint of hardcover 1st ed. 2008
  • Seitenzahl: 528
  • Erscheinungstermin: 19. Oktober 2010
  • Englisch
  • Abmessung: 235mm x 155mm x 28mm
  • Gewicht: 825g
  • ISBN-13: 9783642095153
  • ISBN-10: 3642095151
  • Artikelnr.: 32058225
Inhaltsangabe
Selected issues of artificial intelligence.- Methods of knowledge representation using rough sets.- Methods of knowledge representation using type-1 fuzzy sets.- Methods of knowledge representation using type-2 fuzzy sets.- Neural networks and their learning algorithms.- Evolutionary algorithms.- Data clustering methods.- Neuro-fuzzy systems of Mamdani, logical and Takagi-Sugeno type.- Flexible neuro-fuzzy systems.