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The Harmony Search Algorithm for Supervised Training of Neural Network: Design & Implementation - Softcover
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Within the field of Artificial Intelligence, there are basically two paradigms for the supervised training of Feed-forward Artificial Neural Network (FFANN): the trajectory-driven paradigm, such as Backpropagation, and the evolutionary Stochastic Global Optimization paradigm (SGO), such as Genetic Algorithm. One of the relatively young SGO methods is the Harmony Search (HS) algorithm, which draws its inspiration not from biological or physical processes but from the improvisation process of Jazz musicians. HS was reported to be competitive alternative to other SGO methods. It has been used successfully in many applications mostly in engineering and industry. In this work the HS algorithm is adapted for the supervised training of FFANN and the performance is evaluated using different benchmarking problems. Two enhancements are introduced to achieve better convergence condition and better performance. A parallel implementation is also included along with performance analysis.
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Within the field of Artificial Intelligence, there are basically two paradigms for the supervised training of Feed-forward Artificial Neural Network (FFANN): the trajectory-driven paradigm, such as Backpropagation, and the evolutionary Stochastic Global Optimization paradigm (SGO), such as Genetic Algorithm. One of the relatively young SGO methods is the Harmony Search (HS) algorithm, which draws its inspiration not from biological or physical processes but from the improvisation process of Jazz musicians. HS was reported to be competitive alternative to other SGO methods. It has been used successfully in many applications mostly in engineering and industry. In this work the HS algorithm is adapted for the supervised training of FFANN and the performance is evaluated using different benchmarking problems. Two enhancements are introduced to achieve better convergence condition and better performance. A parallel implementation is also included along with performance analysis.
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The Harmony Search Algorithm for Supervised Training of Neural Network
Verlag:
LAP LAMBERT Academic Publishing, 2019
ISBN 10: 6139472555
ISBN 13: 9786139472550
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Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Kattan AliAli Kattan, a member of IEEE since 2009, is a PhD holder and an Assistant Professor of Computer Sciences. His research interests include machine learning, optimization, robotics, IoT and web programming. He is currently a s. Bestandsnummer des Verkäufers 385860534
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The Harmony Search Algorithm for Supervised Training of Neural Network
Verlag:
LAP LAMBERT Academic Publishing Apr 2019, 2019
ISBN 10: 6139472555
ISBN 13: 9786139472550
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Taschenbuch. Zustand: Neu. Neuware -Within the field of Artificial Intelligence, there are basically two paradigms for the supervised training of Feed-forward Artificial Neural Network (FFANN): the trajectory-driven paradigm, such as Backpropagation, and the evolutionary Stochastic Global Optimization paradigm (SGO), such as Genetic Algorithm. One of the relatively young SGO methods is the Harmony Search (HS) algorithm, which draws its inspiration not from biological or physical processes but from the improvisation process of Jazz musicians. HS was reported to be competitive alternative to other SGO methods. It has been used successfully in many applications mostly in engineering and industry. In this work the HS algorithm is adapted for the supervised training of FFANN and the performance is evaluated using different benchmarking problems. Two enhancements are introduced to achieve better convergence condition and better performance. A parallel implementation is also included along with performance analysis.Books on Demand GmbH, Überseering 33, 22297 Hamburg 260 pp. Englisch. Bestandsnummer des Verkäufers 9786139472550
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The Harmony Search Algorithm for Supervised Training of Neural Network
Verlag:
LAP LAMBERT Academic Publishing Apr 2019, 2019
ISBN 10: 6139472555
ISBN 13: 9786139472550
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Anbieter: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Deutschland
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Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Within the field of Artificial Intelligence, there are basically two paradigms for the supervised training of Feed-forward Artificial Neural Network (FFANN): the trajectory-driven paradigm, such as Backpropagation, and the evolutionary Stochastic Global Optimization paradigm (SGO), such as Genetic Algorithm. One of the relatively young SGO methods is the Harmony Search (HS) algorithm, which draws its inspiration not from biological or physical processes but from the improvisation process of Jazz musicians. HS was reported to be competitive alternative to other SGO methods. It has been used successfully in many applications mostly in engineering and industry. In this work the HS algorithm is adapted for the supervised training of FFANN and the performance is evaluated using different benchmarking problems. Two enhancements are introduced to achieve better convergence condition and better performance. A parallel implementation is also included along with performance analysis. 260 pp. Englisch. Bestandsnummer des Verkäufers 9786139472550
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The Harmony Search Algorithm for Supervised Training of Neural Network : Design & Implementation
Verlag:
LAP LAMBERT Academic Publishing, 2019
ISBN 10: 6139472555
ISBN 13: 9786139472550
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Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Within the field of Artificial Intelligence, there are basically two paradigms for the supervised training of Feed-forward Artificial Neural Network (FFANN): the trajectory-driven paradigm, such as Backpropagation, and the evolutionary Stochastic Global Optimization paradigm (SGO), such as Genetic Algorithm. One of the relatively young SGO methods is the Harmony Search (HS) algorithm, which draws its inspiration not from biological or physical processes but from the improvisation process of Jazz musicians. HS was reported to be competitive alternative to other SGO methods. It has been used successfully in many applications mostly in engineering and industry. In this work the HS algorithm is adapted for the supervised training of FFANN and the performance is evaluated using different benchmarking problems. Two enhancements are introduced to achieve better convergence condition and better performance. A parallel implementation is also included along with performance analysis. Bestandsnummer des Verkäufers 9786139472550
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The Harmony Search Algorithm for Supervised Training of Neural Network: Design & Implementation
Verlag:
LAP LAMBERT Academic Publishing, 2019
ISBN 10: 6139472555
ISBN 13: 9786139472550
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The Harmony Search Algorithm for Supervised Training of Neural Network: Design & Implementation
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ISBN 13: 9786139472550
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The Harmony Search Algorithm for Supervised Training of Neural Network: Design & Implementation
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LAP LAMBERT Academic Publishing, 2019
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ISBN 13: 9786139472550
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The Harmony Search Algorithm for Supervised Training of Neural Network: Design & Implementation
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LAP LAMBERT Academic Publishing, 2019
ISBN 10: 6139472555
ISBN 13: 9786139472550
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Paperback. Zustand: Brand New. 260 pages. 8.66x5.91x0.59 inches. In Stock. Bestandsnummer des Verkäufers zk6139472555
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