Isbn: 9783319343488 - intelligent control: a hybrid approach based on fuzzy logic, neural networks and genetic algorithms: 517 (studies in computational intelligence) (11 resultados)

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    Editorial: Springer, 2016

    3319343483 / 9783319343488

    Serie: Libro 66 de 538 - Studies in Computational Intelligence

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    Condición: New. pp. 299 Softcover reprint of the original 1st ed. 2014 edition NO-PA16APR2015-KAP.

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    3319343483 / 9783319343488

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    Taschenbuch. Condición: Neu. Intelligent Control | A Hybrid Approach Based on Fuzzy Logic, Neural Networks and Genetic Algorithms | Nazmul Siddique | Taschenbuch | xvii | Englisch | 2016 | Springer | EAN 9783319343488 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu. …

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    3319343483 / 9783319343488

    Serie: Libro 66 de 538 - Studies in Computational Intelligence

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    Taschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - Intelligent Control considers non-traditional modelling and control approaches to nonlinear systems. Fuzzy logic, neural networks and evolutionary computing techniques are the main tools used. The book presents a modular switching fuzzy logic controller where a PD-type fuzzy controller is executed first followed by a PI-type fuzzy controller thus improving the performance of the controller compared with a PID-type fuzzy controller. The advantage of the switching-type fuzzy controller is that it uses one rule-base thus minimises the rule-base during execution. A single rule-base is developed by merging the membership functions for change of error of the PD-type controller and sum of error of the PI-type controller. Membership functions are then optimized using evolutionary algorithms. Since the two fuzzy controllers were executed in series, necessary further tuning of the differential and integral scaling factors of the controller is then performed. Neural-network-based tuning for the scaling parameters of the fuzzy controller is then described and finally an evolutionary algorithm is applied to the neurally-tuned-fuzzy controller in which the sigmoidal function shape of the neural network is determined.The important issue of stability is addressed and the text demonstrates empirically that the developed controller was stable within the operating range. The text concludes with ideas for future research to show the reader the potential for further study in this area.Intelligent Control will be of interest to researchers from engineering and computer science backgrounds working in the intelligent and adaptive control.…

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    Editorial: Springer Verlag, 2016

    3319343483 / 9783319343488

    Serie: Libro 66 de 538 - Studies in Computational Intelligence

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    Paperback. Condición: Brand New. reprint edition. 300 pages. 9.25x6.10x0.71 inches. In Stock.

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    Condición: new. Questo è un articolo print on demand.

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    Editorial: Springer International Publishing Aug 2016, 2016

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    Serie: Libro 66 de 538 - Studies in Computational Intelligence

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    Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Intelligent Control considers non-traditional modelling and control approaches to nonlinear systems. Fuzzy logic, neural networks and evolutionary computing techniques are the main tools used. The book presents a modular switching fuzzy logic controller where a PD-type fuzzy controller is executed first followed by a PI-type fuzzy controller thus improving the performance of the controller compared with a PID-type fuzzy controller. The advantage of the switching-type fuzzy controller is that it uses one rule-base thus minimises the rule-base during execution. A single rule-base is developed by merging the membership functions for change of error of the PD-type controller and sum of error of the PI-type controller. Membership functions are then optimized using evolutionary algorithms. Since the two fuzzy controllers were executed in series, necessary further tuning of the differential and integral scaling factors of the controller is then performed. Neural-network-based tuning for the scaling parameters of the fuzzy controller is then described and finally an evolutionary algorithm is applied to the neurally-tuned-fuzzy controller in which the sigmoidal function shape of the neural network is determined.The important issue of stability is addressed and the text demonstrates empirically that the developed controller was stable within the operating range. The text concludes with ideas for future research to show the reader the potential for further study in this area.Intelligent Control will be of interest to researchers from engineering and computer science backgrounds working in the intelligent and adaptive control. 300 pp. Englisch.…

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    Editorial: Springer International Publishing, 2016

    3319343483 / 9783319343488

    Serie: Libro 66 de 538 - Studies in Computational Intelligence

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    Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Nazmul H. Siddique graduated from Dresden University of Technology, Germany in Cybernetics and Automation Engineering in 1989. He obtained M. Sc. Eng. in Computer Science and Engineering from Bangladesh University of Engineering and Technology (BUET) in 199.…

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    Serie: Libro 66 de 538 - Studies in Computational Intelligence

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    Condición: New. Print on Demand pp. 299.

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    3319343483 / 9783319343488

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    Condición: New. PRINT ON DEMAND pp. 299.

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    Editorial: Springer, Palgrave Macmillan Aug 2016, 2016

    3319343483 / 9783319343488

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    Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Intelligent Control considers non-traditional modelling and control approaches to nonlinear systems. Fuzzy logic, neural networks and evolutionary computing techniques are the main tools used. The book presents a modular switching fuzzy logic controller where a PD-type fuzzy controller is executed first followed by a PI-type fuzzy controller thus improving the performance of the controller compared with a PID-type fuzzy controller.The advantage of the switching-type fuzzy controller is that it uses one rule-base thus minimises the rule-base during execution. A single rule-base is developed by merging the membership functions for change of error of the PD-type controller and sum of error of the PI-type controller. Membership functions are then optimized using evolutionary algorithms. Since the two fuzzy controllers were executed in series, necessary further tuning of the differential and integral scaling factors of the controller is then performed. Neural-network-based tuning for the scaling parameters of the fuzzy controller is then described and finally an evolutionary algorithm is applied to the neurally-tuned-fuzzy controller in which the sigmoidal function shape of the neural network is determined.The important issue of stability is addressed and the text demonstrates empirically that the developed controller was stable within the operating range. The text concludes with ideas for future research to show the reader the potential for further study in this area.Intelligent Control will be of interest to researchers from engineering and computer science backgrounds working in the intelligent and adaptive control.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 300 pp. Englisch.…