ISBN: 9780470287194 - evolving intelligent systems: methodology and applications (19 risultati)

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Hardback. Condizione: New. From theory to techniques, the first all-in-one resource for EIS There 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 emerging research field, with a strong emphasis on the balance between novel theoretical results and solutions and practical real-life applications. Explains the following fundamental approaches for developing evolving intelligent systems (EIS): the Hierarchical Prioritized Structure the Participatory Learning Paradigm the Evolving Takagi-Sugeno fuzzy systems (eTS+) the evolving clustering algorithm that stems from the well-known Gustafson-Kessel offline clustering algorithm Emphasizes the importance and increased interest in online processing of data streams Outlines the general strategy of using the fuzzy dynamic clustering as a foundation for evolvable information granulation Presents a methodology for developing robust and interpretable evolving fuzzy rule-based systems Introduces an integrated approach to incremental (real-time) feature extraction and classification Proposes a study on the stability of evolving neuro-fuzzy recurrent networks Details methodologies for evolving clustering and classification Reveals different applications of EIS to address real problems in areas of: evolving inferential sensors in chemical and petrochemical industry learning and recognition in robotics Features downloadable software resources Evolving Intelligent Systems is the one-stop reference guide for both theoretical and practical issues for computer scientists, engineers, researchers, applied mathematicians, machine learning and data mining experts, graduate students, and professionals.…

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Condizione: New. 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. Editor(s): Angelov, Plamen; Filev, Dimitar P.; Kasabov, Nikola K. Series: IEEE Press Series on Computational Intelligence. Num Pages: 444 pages, Illustrations. BIC Classification: UYQ. Category: (P) Professional & Vocational. Dimension: 241 x 158 x 29. Weight in Grams: 780. . 2010. 1st Edition. Hardcover. . . . .…

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Condizione: New. 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.

Hardcover. Condizione: Brand New. 1st edition. 444 pages. 9.41x6.46x1.18 inches. In Stock.

Condizione: New. 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. Editor(s): Angelov, Plamen; Filev, Dimitar P.; Kasabov, Nikola K. Series: IEEE Press Series on Computational Intelligence. Num Pages: 444 pages, Illustrations. BIC Classification: UYQ. Category: (P) Professional & Vocational. Dimension: 241 x 158 x 29. Weight in Grams: 780. . 2010. 1st Edition. Hardcover. . . . . Books ship from the US and Ireland.…

Buch. Condizione: Neu. Neuware - 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 emerging research field, with a strong emphasis on the balance between novel theoretical results and solutions and practical real-life applications.\* Explains the following fundamental approaches for developing evolving intelligent systems (EIS):\* the Hierarchical Prioritized Structure\* the Participatory Learning Paradigm\* the Evolving Takagi-Sugeno fuzzy systems (eTS+)\* the evolving clustering algorithm that stems from the well-known Gustafson-Kessel offline clustering algorithm\* Emphasizes the importance and increased interest in online processing of data streams\* Outlines the general strategy of using the fuzzy dynamic clustering as a foundation for evolvable information granulation\* Presents a methodology for developing robust and interpretable evolving fuzzy rule-based systems\* Introduces an integrated approach to incremental (real-time) feature extraction and classification\* Proposes a study on the stability of evolving neuro-fuzzy recurrent networks\* Details methodologies for evolving clustering and classification\* Reveals different applications of EIS to address real problems in areas of:\* evolving inferential sensors in chemical and petrochemical industry\* learning and recognition in robotics\* Features downloadable software resourcesEvolving Intelligent Systems is the one-stop reference guide for both theoretical and practical issues for computer scientists, engineers, researchers, applied mathematicians, machine learning and data mining experts, graduate students, and professionals.…

Hardback. Condizione: New. From theory to techniques, the first all-in-one resource for EIS There 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 emerging research field, with a strong emphasis on the balance between novel theoretical results and solutions and practical real-life applications. Explains the following fundamental approaches for developing evolving intelligent systems (EIS): the Hierarchical Prioritized Structure the Participatory Learning Paradigm the Evolving Takagi-Sugeno fuzzy systems (eTS+) the evolving clustering algorithm that stems from the well-known Gustafson-Kessel offline clustering algorithm Emphasizes the importance and increased interest in online processing of data streams Outlines the general strategy of using the fuzzy dynamic clustering as a foundation for evolvable information granulation Presents a methodology for developing robust and interpretable evolving fuzzy rule-based systems Introduces an integrated approach to incremental (real-time) feature extraction and classification Proposes a study on the stability of evolving neuro-fuzzy recurrent networks Details methodologies for evolving clustering and classification Reveals different applications of EIS to address real problems in areas of: evolving inferential sensors in chemical and petrochemical industry learning and recognition in robotics Features downloadable software resources Evolving Intelligent Systems is the one-stop reference guide for both theoretical and practical issues for computer scientists, engineers, researchers, applied mathematicians, machine learning and data mining experts, graduate students, and professionals.…