Evolving Intelligent Systems - Methodology and ications
Published on 14. April 2010
Software
Other digital
464 pages
978-0-470-56996-2 (ISBN)
Description
This is the first self-contained book that covers the topic of Evolving Intelligent Systems in its entirety, from a systematic methodology to case studies and real industrial applications. There is a clear demand for a treatment of this topic in advanced process industries, defense, and Internet and communication (VoIP) applications for intelligent yet adaptive/evolving systems. The book targets researchers, engineers, postgraduate students, and practitioners in advanced process industries, applied mathematicians, software developers of agent-oriented systems, and developers of embedded and real-time systems.
More details
Language
English
Place of publication
Hoboken
United Kingdom
Publishing group
John Wiley and Sons Ltd
Target group
Professional and scholarly
ISBN-13
978-0-470-56996-2 (9780470569962)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions
Plamen Angelov | Dimitar P. Filev | Nik Kasabov
Evolving Intelligent Systems
Methodology and Applications
E-Book
03/2010
Wiley-IEEE Press
€134.99
Available for download
Persons
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 Systems, Man, and Cybernetics Society and?past president of the North American 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).
Content
PREFACE. Evolving Intelligent Systems. The Editors. PART I: METHODOLOGY. Evolving Fuzzy Systems. 1. Learning Methods for Evolving Intelligent Systems ( R. Yager ). 2. Evolving Takagi-Sugeno Fuzzy Systems from Data Streams (eTS+) ( P. Angelov ). 3. Fuzzy Models of Evolvable Granularity ( W. Pedrycz ). 4. Evolving Fuzzy Modeling Using Participatory Learning ( E. Lima, M. Hell, R. Ballini, and F. Gomide ). 5. Towards Robust and Transparent Evolving Fuzzy Systems ( E. Lughofer ). 6. The building of fuzzy systems in real-time: towards interpretable fuzzy rules ( A. Dourado, C. Pereira, and V. Ramos ). Evolving Neuro-Fuzzy Systems. 7. On-line Feature Selection for Evolving Intelligent Systems ( S. Ozawa, S. Pang, and N. Kasabov ). 8. Stability Analysis of an On-Line Evolving Neuro-Fuzzy Network ( J. de J. Rubio Avila ). 9. On-line Identification of Self-organizing Fuzzy Neural Networks for Modelling Time-varying Complex Systems ( G. Prasad, T. M. McGinnity, and G. Leng ). 10. Data Fusion via Fission for the Analysis of Brain Death ( L. Li, Y. Saito, D. Looney, T. Tanaka, J. Cao, and D. Mandic ). Evolving Fuzzy Clustering and Classification. 11. Similarity Analysis and Knowledge Acquisition by Use of Evolving Neural Models and Fuzzy Decision ( G. Vachkov ). 12. An Extended version of Gustafson-Kessel Clustering Algorithm for Evolving Data Stream Clustering ( D. Filev, and O. Georgieva ). 13. Evolving Fuzzy Classification of Non-Stationary Time Series (Y. Bodyanskiy, Y. Gorshkov, I. Kokshenev, and V. Kolodyazhniy). PART II: APPLICATIONS OF EIS. 14. Evolving Intelligent Sensors in Chemical Industry ( A. Kordon et al. ). 15. Recognition of Human Grasps by Fuzzy Modeling (R Palm, B Kadmiry, and B Iliev). 16. Evolutionary Architecture for Lifelong Learning and Real-time Operation in Autonomous Robots ( R. J. Duro, F. Bellas and J.A. Becerra ) 17. Applications of Evolving Intelligent Systems to Oil and Gas Industry ( J. J. Macias Hernandez et al. ). Conclusion.