9780470287194 - evolving intelligent systems: methodology and applications: 12 (ieee press series on computational intelligence) (18 resultados)
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Librería: ThriftBooks-Dallas, Dallas, TX, Estados Unidos de AmericaThriftBooks-Dallas
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Hardcover. Condición: Very Good. No Jacket. Former library book; May have limited writing in cover pages. Pages are unmarked. ~ ThriftBooks: Read More, Spend Less.
Evolving Intelligent Systems : Methodology and Applications
Angelov, Plamen (EDT); Filev, Dimitar P. (EDT); Kasabov, Nikola K. (EDT)
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Condición: Good. Your purchase helps support Sri Lankan Children's Charity 'The Rainbow Centre'. Ex-library, so some stamps and wear, but in good overall condition. Our donations to The Rainbow Centre have helped provide an education and a safe haven to hundreds of children who live in appalling conditions.
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Evolving Intelligent Systems : Methodology and Applications
Angelov, Plamen (EDT); Filev, Dimitar P. (EDT); Kasabov, Nikola K. (EDT)
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Librería: GreatBookPrices, Columbia, MD, Estados Unidos de AmericaGreatBookPrices
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HRD. Condición: New. New Book. Shipped from UK. Established seller since 2000.
Evolving Intelligent Systems : Methodology and Applications
Angelov, Plamen (EDT); Filev, Dimitar P. (EDT); Kasabov, Nikola K. (EDT)
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Librería: GreatBookPricesUK, Woodford Green, Reino UnidoGreatBookPricesUK
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Evolving Intelligent Systems : Methodology and Applications
Angelov, Plamen (EDT); Filev, Dimitar P. (EDT); Kasabov, Nikola K. (EDT)
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Hardback. Condición: 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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Condición: New. In English.
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Librería: Kennys Bookshop and Art Galleries Ltd., Galway, GY, IrlandaKennys Bookshop and Art Galleries Ltd.
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EUR 173,25
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Condición: 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. Nu…m 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. . . . .
Evolving Intelligent Systems Methodology and Applications
Angelov, Plamen (Editor)/ Filev, Dimitar P. (Editor)/ Kasabov, Nik (Editor)
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Hardcover. Condición: Brand New. 1st edition. 444 pages. 9.41x6.46x1.18 inches. In Stock.
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EUR 212,72
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Condición: 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. Nu…m 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.
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Hardback. Condición: 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.
