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Evolving Intelligent Systems : Methodology and Applications

ISBN: 9780470287194 | 0470287195
Edition: 1st
Format: Hardcover
Publisher: Wiley-IEEE Press
Pub. Date: 3/22/2010

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SummaryTable of ContentsAuthor Biography
From theory to techniques, the first all-in-one resource for EISThere is a clear demand in advanced process industries, defense, and Internet and communication (VoIP) applications for intelligent yet adaptive/evolving systems. Evolving Intelligent Systems is the first self- contained volume that covers this newly established concept in its entirety, from a systematic methodology to case studies to industrial applications. Featuring chapters written by leading world experts, it addresses the progress, trends, and major achievements in this emerg... MORE
Learning Methods for Evolving Intelligent Systemsp. 1
Evolving Takagi-Sugeno Fuzzy Systems from Streaming Data (eTS+)p. 21
Fuzzy Models of Evolvable Granularityp. 51
Evolving Fuzzy Modeling Using Participatory Learningp. 67
Toward Robust Evolving Fuzzy Systemsp. 87
Building Interpretable Systems in Real Timep. 127
Online Feature Extraction for Evolving Intelligent Systems... MOREp. 151
Stability Analysis for an Online Evolving Neuro-Fuzzy Recurrent Networkp. 173
Online Identification of Self-Organizing Fizzy Neural Networks for Modeling Time-Varying Complex Systemsp. 201
Data Fusion Via Fission for the Analysis of Brain Deathp. 229
Similarity Analysis and Knowledge Acquisition by use of Evolving Neural Models and Fuzzy Decisionp. 247
An Extended Version of The Gustafson-Kessel Algorithm for Evolving Data Stream Clusteringp. 273
Evolving Fuzzy Classification of Nonstationary Time Seriesp. 301
Evolving Inferential Sensors in The Chemical Process Industryp. 313
Recognition of Human Grasp By Fuzzy Modelingp. 337
Evolutionary Architecture for Lifelong Learning and Real-Time Operation in Autonomous Robotsp. 365
Applications of Evolving Intelligent Systems To Oil and Gas Industryp. 401
Epiloguep. 423
About the Editorsp. 425
About the Contributorsp. 427
Indexp. 439
Table of Contents provided by Ingram. All Rights Reserved.
Plamen Angelov, PhD, is with the Department of communication Systems, Lancaster University. He is a member of the Fuzzy Systems Technical Committee, the founding Chair of the Adaptive Fuzzy Systems Task Force to the Computational Intelligence Society, and a Senior Member of IEEE. Dimitar P. Filev, PhD, is a Senior Technical Leader, Intelligent Control Information Systems, with Ford Research Advanced Engineering and a Fellow of IEEE. He is a Vice President for Cybernetics of the IEEE System, Man, and Cybernetics Society and past president of the North Americana Fuzzy Information Processing Society (NAFIPS). Nikola Kasabov is the Director of the Knowledge Engineering and Discovery Research Institute (KEDRI). He holds a Chair of Knowledge Engineering at the School of Computer and Information Sciences at Auckland University of Technology. He is a Fellow of IEEE, Fellow of the Royal Society of New Zealand, Fellow of the New Zealand Computer Society, and the President of the International Neural Network Society (INNS)


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