Rutkowski Computational Intelligence

Methods and Techniques
1. Auflage 2008
ISBN: 978-3-540-76288-1
Verlag: Springer
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 514 Seiten, eBook

Publication of this book is a special event. This valuable title ?lls a se- ous gap in domestic science and technical literature. At the same time it introduces a reader to the most recent achievements in the quickly dev- oping branch of knowledge which the computational intelligence has been for several years. The ?eld, which is a subject of this book, is one of those important ?elds of science which enable to process information included in data and give their reasonable interpretation programmed by a user. Recent decades have brought a stormy development of computer te- niquesandrelatedcomputationalmethods.Togetherwiththeirappearance and quick progress, theoretical and applied sciences developed as well, - ablingtheusertofullyutilizenewlycreatedcomputationalpotentialandto getknowledgeoutofincreasingwealthofdata.Thedevelopmentofcom- tational intelligence is then strictly connected with the increase of available data as well as capabilities of their processing, mutually supportive factors. Without them the development of this ?eld would be almost impossible, and its application practically marginal. That is why these techniques have especially developed in recent years. The development of computational intelligence systems was inspired by observable and imitable aspects of intelligent activity of human being and nature. Nature when undertakes intelligent actions processes data in p- allel regulating and adjusting these actions through feedback mechanisms.

Zielgruppe

Research

Autoren/Hrsg.

Rutkowski, Leszek

Inhaltsverzeichnis

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.