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Evolving Rule-Based Models: A Tool for Design of Flexible Adaptive Systems - libro nuevo

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The idea about this book has evolved during the process of its preparation as some of the results have been achieved in parallel with its writing. One reason for this is that in this area… Más…

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Evolving Rule-Based Models A Tool for Design of Flexible Adaptive Systems - Pasta blanda

2010, ISBN: 3790825069

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Softcover reprint of hardcover 1st ed. 2002 Kartoniert / Broschiert Mathematische Grundlagen, Mathematik: Logik, Mathematik für Ingenieure, Künstliche Intelligenz, algorithms; complexsy… Más…

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Plamen P. Angelov:
Evolving Rule-Based Models: A Tool for Design of Flexible Adaptive Systems (Studies in Fuzziness and Soft Computing) - Pasta blanda

2010

ISBN: 9783790825060

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Physica, 2010-12-15. Softcover reprint of hardcover 1. Paperback. Used:Good., Physica, 2010-12-15

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Plamen P. Angelov:
Evolving Rule-Based Models: A Tool for Design of Flexible Adaptive Systems (Studies in Fuzziness and Soft Computing) - Pasta blanda

2010, ISBN: 9783790825060

Physica-Verlag HD, 2010-12-15. Paperback. Good., Physica-Verlag HD, 2010-12-15

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Plamen P. Angelov:
Evolving Rule-Based Models - libro nuevo

ISBN: 9783790825060

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Detalles del libro
Evolving Rule-Based Models: A Tool for Design of Flexible Adaptive Systems

The objects of modelling and control change due to dynamical characteristics, fault development or simply ageing. There is a need to up-date models inheriting useful structure and parameter information. The book gives an original solution to this problem with a number of examples. It treats an original approach to on-line adaptation of rule-based models and systems described by such models. It combines the benefits of fuzzy rule-based models suitable for the description of highly complex systems with the original recursive, non iterative technique of model evolution without necessarily using genetic algorithms, thus avoiding computational burden making possible real-time industrial applications. Potential applications range from autonomous systems, on-line fault detection and diagnosis, performance analysis to evolving (self-learning) intelligent decision support systems.

Detalles del libro - Evolving Rule-Based Models: A Tool for Design of Flexible Adaptive Systems


EAN (ISBN-13): 9783790825060
ISBN (ISBN-10): 3790825069
Tapa dura
Tapa blanda
Año de publicación: 2010
Editorial: Physica
228 Páginas
Peso: 0,351 kg
Idioma: eng/Englisch

Libro en la base de datos desde 2011-07-29T10:14:14-05:00 (Mexico City)
Página de detalles modificada por última vez el 2023-10-10T13:32:45-06:00 (Mexico City)
ISBN/EAN: 9783790825060

ISBN - escritura alterna:
3-7908-2506-9, 978-3-7908-2506-0
Mode alterno de escritura y términos de búsqueda relacionados:
Autor del libro: angelov
Título del libro: rule, systems art, flexible design


Datos del la editorial

Autor: Plamen P. Angelov
Título: Studies in Fuzziness and Soft Computing; Evolving Rule-Based Models - A Tool for Design of Flexible Adaptive Systems
Editorial: Physica; Physica
214 Páginas
Año de publicación: 2010-10-21
Heidelberg; DE
Impreso en
Idioma: Inglés
106,99 € (DE)
109,99 € (AT)
118,00 CHF (CH)
POD
XIII, 214 p.

BC; Hardcover, Softcover / Mathematik/Grundlagen; Mathematik: Logik; Verstehen; algorithms; complex system; complex systems; decision support system; fuzzy; genetic algorithms; model; modeling; system; complexity; Mathematical Logic and Foundations; Systems Theory, Control; Artificial Intelligence; Applied Dynamical Systems; Mathematische Grundlagen; Kybernetik und Systemtheorie; Künstliche Intelligenz; Mathematik für Ingenieure; BB

The objects of modelling and control change due to dynamical characteristics, fault development or simply ageing. There is a need to up-date models inheriting useful structure and parameter information. The book gives an original solution to this problem with a number of examples. It treats an original approach to on-line adaptation of rule-based models and systems described by such models. It combines the benefits of fuzzy rule-based models suitable for the description of highly complex systems with the original recursive, non iterative technique of model evolution without necessarily using genetic algorithms, thus avoiding computational burden making possible real-time industrial applications. Potential applications range from autonomous systems, on-line fault detection and diagnosis, performance analysis to evolving (self-learning) intelligent decision support systems.
First approach to on-line generation and adaptation of rule-based models Illustration with real engineering examples Includes supplementary material: sn.pub/extras

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