Librería: Ria Christie Collections, Uxbridge, Reino Unido
EUR 127,89
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Librería: Ria Christie Collections, Uxbridge, Reino Unido
EUR 127,89
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Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
EUR 120,31
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Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
EUR 120,32
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Publicado por Springer International Publishing, Springer International Publishing, 2019
ISBN 10: 3030065723 ISBN 13: 9783030065720
Idioma: Inglés
Librería: AHA-BUCH GmbH, Einbeck, Alemania
EUR 128,39
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Añadir al carritoTaschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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.
Publicado por Springer International Publishing, 2018
ISBN 10: 3319930249 ISBN 13: 9783319930244
Idioma: Inglés
Librería: AHA-BUCH GmbH, Einbeck, Alemania
EUR 128,39
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Añadir al carritoBuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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.
Librería: GreatBookPricesUK, Woodford Green, Reino Unido
EUR 127,88
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Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
EUR 138,98
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Librería: California Books, Miami, FL, Estados Unidos de America
EUR 150,03
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Librería: GreatBookPricesUK, Woodford Green, Reino Unido
EUR 140,72
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Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
EUR 143,22
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Librería: Books Puddle, New York, NY, Estados Unidos de America
EUR 162,13
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Librería: Books Puddle, New York, NY, Estados Unidos de America
EUR 164,21
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Librería: Lucky's Textbooks, Dallas, TX, Estados Unidos de America
EUR 121,40
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Librería: Lucky's Textbooks, Dallas, TX, Estados Unidos de America
EUR 121,74
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Publicado por Springer Nature Switzerland AG, Cham, 2019
ISBN 10: 3030065723 ISBN 13: 9783030065720
Idioma: Inglés
Librería: Grand Eagle Retail, Bensenville, IL, Estados Unidos de America
EUR 122,65
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Añadir al carritoPaperback. Condición: new. Paperback. 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.
Publicado por Springer International Publishing AG, Cham, 2018
ISBN 10: 3319930249 ISBN 13: 9783319930244
Idioma: Inglés
Librería: Grand Eagle Retail, Bensenville, IL, Estados Unidos de America
Original o primera edición
EUR 122,67
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Añadir al carritoHardcover. Condición: 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.
Librería: Revaluation Books, Exeter, Reino Unido
EUR 179,41
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Añadir al carritoHardcover. Condición: Brand New. 156 pages. 9.50x6.25x0.50 inches. In Stock.
Librería: Mispah books, Redhill, SURRE, Reino Unido
EUR 187,06
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Publicado por Springer International Publishing AG, Cham, 2018
ISBN 10: 3319930249 ISBN 13: 9783319930244
Idioma: Inglés
Librería: AussieBookSeller, Truganina, VIC, Australia
Original o primera edición
EUR 218,48
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Añadir al carritoHardcover. Condición: 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.
Publicado por Springer Nature Switzerland AG, Cham, 2019
ISBN 10: 3030065723 ISBN 13: 9783030065720
Idioma: Inglés
Librería: AussieBookSeller, Truganina, VIC, Australia
EUR 218,48
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Añadir al carritoPaperback. Condición: new. Paperback. 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.
Publicado por Springer International Publishing, 2018
ISBN 10: 3319930249 ISBN 13: 9783319930244
Idioma: Inglés
Librería: moluna, Greven, Alemania
EUR 109,83
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Añadir al carritoCondición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Introduces beginners to evolutionary algorithms and artificial neural networks Shows how to train artificial neural networks using evolutionary algorithmsIncludes extensive examples of the propos.
Publicado por Springer International Publishing, 2019
ISBN 10: 3030065723 ISBN 13: 9783030065720
Idioma: Inglés
Librería: moluna, Greven, Alemania
EUR 109,83
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Añadir al carritoCondición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Introduces beginners to evolutionary algorithms and artificial neural networks Shows how to train artificial neural networks using evolutionary algorithmsIncludes extensive examples of the propos.
Publicado por Springer International Publishing Jul 2018, 2018
ISBN 10: 3319930249 ISBN 13: 9783319930244
Idioma: Inglés
Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
EUR 128,39
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Añadir al carritoBuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 172 pp. Englisch.
Publicado por Springer International Publishing Jan 2019, 2019
ISBN 10: 3030065723 ISBN 13: 9783030065720
Idioma: Inglés
Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
EUR 128,39
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Añadir al carritoTaschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 172 pp. Englisch.
Publicado por Springer International Publishing, Springer International Publishing Jan 2019, 2019
ISBN 10: 3030065723 ISBN 13: 9783030065720
Idioma: Inglés
Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemania
EUR 128,39
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Añadir al carritoTaschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -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.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 172 pp. Englisch.
Publicado por Springer International Publishing, Springer International Publishing Jul 2018, 2018
ISBN 10: 3319930249 ISBN 13: 9783319930244
Idioma: Inglés
Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemania
EUR 128,39
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Añadir al carritoBuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -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.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 172 pp. Englisch.
Librería: Majestic Books, Hounslow, Reino Unido
EUR 170,69
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Librería: Majestic Books, Hounslow, Reino Unido
EUR 172,56
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Librería: Biblios, Frankfurt am main, HESSE, Alemania
EUR 172,91
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