Evolutionary Algorithms and Neural Networks: Theory and Applications (Studies in Computational Intelligence, 780)
Mirjalili, Seyedali
ISBN 10: 3319930249 ISBN 13: 9783319930244
Editore: Springer, 2018
Usato
Hardcover
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SpringBooks, Berlin, Germania
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Unread, some shelfwear. Immediately dispatched from Germany. Codice articolo CEA-2408C-WISENT-15-0500k
Riassunto:
This book introduces readers to the fundamentals of artificial neural networks, with a special emphasis on evolutionary algorithms. At first, the book offers a literature review of several well-regarded evolutionary algorithms, including particle swarm and ant colony optimization, genetic algorithms and biogeography-based optimization. It then proposes evolutionary version of several types of neural networks such as feed forward neural networks, radial basis function networks, as well as recurrent neural networks and multi-later perceptron. Most of the challenges that have to be addressed when training artificial neural networks using evolutionary algorithms are discussed in detail. The book also demonstrates the application of the proposed algorithms for several purposes such as classification, clustering, approximation, and prediction problems. It provides a tutorial on how to design, adapt, and evaluate artificial neural networks as well, and includes source codes for most of the proposed techniques as supplementary materials.
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Titolo: Evolutionary Algorithms and Neural Networks:...
Casa editrice: Springer
Data di pubblicazione: 2018
Legatura: Hardcover
Condizione: Very Good
Edizione: 1. Auflage
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Evolutionary Algorithms and Neural Networks (Hardcover)
Editore:
Springer International Publishing AG, Cham, 2018
ISBN 10: 3319930249
ISBN 13: 9783319930244
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Da: Grand Eagle Retail, Mason, OH, U.S.A.
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Hardcover. Condizione: new. Hardcover. This book introduces readers to the fundamentals of artificial neural networks, with a special emphasis on evolutionary algorithms. At first, the book offers a literature review of several well-regarded evolutionary algorithms, including particle swarm and ant colony optimization, genetic algorithms and biogeography-based optimization. It then proposes evolutionary version of several types of neural networks such as feed forward neural networks, radial basis function networks, as well as recurrent neural networks and multi-later perceptron. Most of the challenges that have to be addressed when training artificial neural networks using evolutionary algorithms are discussed in detail. The book also demonstrates the application of the proposed algorithms for several purposes such as classification, clustering, approximation, and prediction problems. It provides a tutorial on how to design, adapt, and evaluate artificial neural networks as well, and includes source codes for most of the proposed techniques as supplementary materials. This book introduces readers to the fundamentals of artificial neural networks, with a special emphasis on evolutionary algorithms. It then proposes evolutionary version of several types of neural networks such as feed forward neural networks, radial basis function networks, as well as recurrent neural networks and multi-later perceptron. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Codice articolo 9783319930244
Quantità: 1 disponibili
Foto dell'editore
Evolutionary Algorithms and Neural Networks (Hardcover)
Editore:
Springer International Publishing AG, Cham, 2018
ISBN 10: 3319930249
ISBN 13: 9783319930244
Nuovo
Rilegato
Prima edizione
Da: AussieBookSeller, Truganina, VIC, Australia
Valutazione del venditore 5 su 5 stelle
Hardcover. Condizione: new. Hardcover. This book introduces readers to the fundamentals of artificial neural networks, with a special emphasis on evolutionary algorithms. At first, the book offers a literature review of several well-regarded evolutionary algorithms, including particle swarm and ant colony optimization, genetic algorithms and biogeography-based optimization. It then proposes evolutionary version of several types of neural networks such as feed forward neural networks, radial basis function networks, as well as recurrent neural networks and multi-later perceptron. Most of the challenges that have to be addressed when training artificial neural networks using evolutionary algorithms are discussed in detail. The book also demonstrates the application of the proposed algorithms for several purposes such as classification, clustering, approximation, and prediction problems. It provides a tutorial on how to design, adapt, and evaluate artificial neural networks as well, and includes source codes for most of the proposed techniques as supplementary materials. This book introduces readers to the fundamentals of artificial neural networks, with a special emphasis on evolutionary algorithms. It then proposes evolutionary version of several types of neural networks such as feed forward neural networks, radial basis function networks, as well as recurrent neural networks and multi-later perceptron. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability. Codice articolo 9783319930244
Quantità: 1 disponibili