Computational Intelligence: Methods and Techniques

Rutkowski, Leszek

ISBN 10: 3642095151 / ISBN 13: 9783642095153

Published by Springer, 2010

About this Item

514 pp., Paperback, previous owner's name neatly inked to the title page, else fine. - If you are reading this, this item is actually (physically) in our stock and ready for shipment once ordered. We are not bookjackers. Buyer is responsible for any additional duties, taxes, or fees required by recipient's country.

Seller Inventory # ZB1314858

Bibliographic Details

• Title: Computational Intelligence: Methods and Techniques
• Publisher: Springer
• Publication Date: 2010
• Language: English
• ISBN 10: 3642095151
• ISBN 13: 9783642095153
• Binding: Soft cover
• Condition: Fine

About this title

Synopsis

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, for example in the processing of speech and natural language, and in building 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 up, various neural network architectures are presented and their learning algorithms are derived. Then, 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.

From the Back Cover

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).