Fuzzy Evolutionary Computation - Hardcover

Hardcover

ISBN 10: 0792399420 ISBN 13: 9780792399421

Publisher: Kluwer Academic Publishers, 1997

Synopsis

As of today, Evolutionary Computing and Fuzzy Set Computing are two mature, wen -developed, and higbly advanced technologies of information processing. Bach of them has its own clearly defined research agenda, specific goals to be achieved, and a wen setUed algorithmic environment. Concisely speaking, Evolutionary Computing (EC) is aimed at a coherent population -oriented methodology of structural and parametric optimization of a diversity of systems. In addition to this broad spectrum of such optimization applications, this paradigm otTers an important ability to cope with realistic goals and design objectives reflected in the form of relevant fitness functions. The GA search (which is often regarded as a dominant domain among other techniques of EC such as evolutionary strategies, genetic programming or evolutionary programming) delivers a great deal of efficiency helping navigate through large search spaces. The main thrust of fuzzy sets is in representing and managing nonnumeric (linguistic) information. The key notion (whose conceptual as weH as algorithmic importance has started to increase in the recent years) is that of information granularity. It somewhat concurs with the principle of incompatibility coined by L. A. Zadeh. Fuzzy sets form a vehic1e helpful in expressing a granular character of information to be captured. Once quantified via fuzzy sets or fuzzy relations, the domain knowledge could be used efficiently very often reducing a heavy computation burden when analyzing and optimizing complex systems.

About this title

Synopsis

The main theme of this text is to highlight a synergistic effect that is emerging between fuzzy sets and evolutionary computation. This quantifies the main advantage arising from the symbiosis. The scope of the book is broad, ranging from coverage of fundamental ideas in fuzzy sets and evolutionary computation, through inclusion of cutting-edge research, to case studies. The focus is on the applied side of fuzzy evolutionary calculations. Each contribution is systematic and thorough in its presentations, and emphasizes design of evolutionary schemes that embraces various sources of domain knowledge. The authors have also included problem sets at the end of each chapter which explore specific conceptual and algorithmic points covered in the text.

Edition details

• Publisher: Kluwer Academic Publishers
• Publication date: 1997
• Language: English
• ISBN 10: 0792399420
• ISBN 13: 9780792399421
• Binding: Hardcover
• Number of pages: 335
• Editor: Pedrycz Witold