Fuzzy Systems Conference (FUZZ), 2000
Author: IEEE Neural Networks Council
Publisher: Institute of Electrical & Electronics Engineers(IEEE)
Published: 2000-05
Total Pages: 576
ISBN-13: 9780780358775
DOWNLOAD EBOOK →Author: IEEE Neural Networks Council
Publisher: Institute of Electrical & Electronics Engineers(IEEE)
Published: 2000-05
Total Pages: 576
ISBN-13: 9780780358775
DOWNLOAD EBOOK →Author: IEEE Neural Networks Council
Publisher: Institute of Electrical & Electronics Engineers(IEEE)
Published: 2000-05
Total Pages: 1122
ISBN-13: 9780780358775
DOWNLOAD EBOOK →Author: IEEE Neural Networks Council
Publisher: IEEE Computer Society Press
Published: 2000
Total Pages: 1080
ISBN-13: 9780780358782
DOWNLOAD EBOOK →Author: International Conference on Fuzzy Systems
Publisher:
Published: 2000
Total Pages:
ISBN-13: 9780780363243
DOWNLOAD EBOOK →Author: Bernadette Bouchon-Meunier
Publisher: Physica
Published: 2013-03-20
Total Pages: 404
ISBN-13: 379081797X
DOWNLOAD EBOOK →Intelligent systems enhance the capacities made available by the internet and other computer-based technologies. This book deals with the theory behind the solutions to difficult problems in the construction of intelligent systems. Particular attention is paid to situations in which the available information and data may be imprecise, uncertain, incomplete or of linguistic nature. Various methodologies for these cases are discussed, among which are probabilistic, possibilistic, fuzzy, logical, evidential and network-based frameworks. One purpose of the book is to consider how these methods can be used cooperatively. Topics included in the book include fundamental issues in uncertainty, the rapidly emerging discipline of information aggregation, neural networks, bayesian networks and other network methods, as well as logic-based systems.
Author: Oscar Cord¢n
Publisher: World Scientific
Published: 2001
Total Pages: 492
ISBN-13: 9789810240172
DOWNLOAD EBOOK →In recent years, a great number of publications have explored the use of genetic algorithms as a tool for designing fuzzy systems. Genetic Fuzzy Systems explores and discusses this symbiosis of evolutionary computation and fuzzy logic. The book summarizes and analyzes the novel field of genetic fuzzy systems, paying special attention to genetic algorithms that adapt and learn the knowledge base of a fuzzy-rule-based system. It introduces the general concepts, foundations and design principles of genetic fuzzy systems and covers the topic of genetic tuning of fuzzy systems. It also introduces the three fundamental approaches to genetic learning processes in fuzzy systems: the Michigan, Pittsburgh and Iterative-learning methods. Finally, it explores hybrid genetic fuzzy systems such as genetic fuzzy clustering or genetic neuro-fuzzy systems and describes a number of applications from different areas. Genetic Fuzzy System represents a comprehensive treatise on the design of the fuzzy-rule-based systems using genetic algorithms, both from a theoretical and a practical perspective. It is a valuable compendium for scientists and engineers concerned with research and applications in the domain of fuzzy systems and genetic algorithms.