Computational Intelligence: Methods and Techniques
Autor Leszek Rutkowskien Limba Engleză Hardback – 29 mai 2008
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Specificații
ISBN-13: 9783540762874
ISBN-10: 3540762876
Pagini: 532
Ilustrații: XIV, 514 p. 242 illus.
Dimensiuni: 155 x 235 x 34 mm
Greutate: 0.89 kg
Ediția:2008
Editura: Springer Berlin, Heidelberg
Colecția Springer
Locul publicării:Berlin, Heidelberg, Germany
ISBN-10: 3540762876
Pagini: 532
Ilustrații: XIV, 514 p. 242 illus.
Dimensiuni: 155 x 235 x 34 mm
Greutate: 0.89 kg
Ediția:2008
Editura: Springer Berlin, Heidelberg
Colecția Springer
Locul publicării:Berlin, Heidelberg, Germany
Public țintă
ResearchCuprins
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.
Textul de pe ultima copertă
This book focuses on various techniques of computational intelligence, both single ones and those which form hybrid methods. Those techniques are today commonly applied issues of artificial intelligence, e.g. to process speech and natural language, build expert systems and robots. The first part of the book presents methods of knowledge representation using different techniques, namely the rough sets, type-1 fuzzy sets and type-2 fuzzy sets. Next various neural network architectures are presented and their learning algorithms are derived. Moreover, the family of evolutionary algorithms is discussed, in particular the classical genetic algorithm, evolutionary strategies and genetic programming, including connections between these techniques and neural networks and fuzzy systems. In the last part of the book, various methods of data partitioning and algorithms of automatic data clustering are given and new neuro-fuzzy architectures are studied and compared. This well-organized modern approach to methods and techniques of intelligent calculations includes examples and exercises in each chapter and a preface by Jacek Zurada, president of IEEE Computational Intelligence Society (2004-05).
Caracteristici
Self-contained, easy accessible and comprehensive textbook for graduate students and researchers in computational intelligence Well-organized modern approach to methods and techniques of intelligent calculations including examples and exercises in each chapter Includes a preface by Jacek Zurada, president of IEEE Computational Intelligence Society Rich and well structured compendium of information about computational intelligence Topics include approximate and fuzzy sets, basic structures and methods of neural networks learning, grouping of data methods, Bayesian methods, evolutionary algorithms and decision tree algorithms