Metaheuristic Procedures for Training Neural Networks. Questo articolo non è disponibile.
Lingua: inglese
Editore: Springer Us Mai 2006, 2006
Serie: Libro 6 di 35 - Operations Research/Computer Science Interfaces
- Rilegato
- Nuovo

Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH
Venditore AbeBooks dal 14 agosto 2006
Condizione: Nuovo
EUR 153,14
Descrizione dell’articolo da parte del venditore
Neuware - Metaheuristic Procedures For Training Neural Networks provides successful implementations of metaheuristic methods for neural network training. Moreover, the basic principles and fundamental ideas given in the book will allow the readers to create successful training methods on their own. Apart from Chapter 1, which reviews classical training methods, the chapters are divided into three main categories. The first one is devoted to local search based methods, including Simulated Annealing, Tabu Search, and Variable Neighborhood Search. The second part of the book presents population based methods, such as Estimation Distribution algorithms, Scatter Search, and Genetic Algorithms. The third part covers other advanced techniques, such as Ant Colony Optimization, Co-evolutionary methods, GRASP, and Memetic algorithms. Overall, the book's objective is engineered to provide a broad coverage of the concepts, methods, and tools of this important area of ANNs within the realm of continuous optimization.…
Codice articolo 9780387334158
- Titolo
- Metaheuristic Procedures for Training Neural Networks
- Autore
- Enrique Alba
- Editore
- Springer Us Mai 2006
- Anno di pubblicazione
- 2006
- Condizione
- Neu
- Rilegatura
- Buch
- Lingua
- inglese
- ISBN 10
- 0387334157
- ISBN 13
- 9780387334158
- Peso dell'articolo
- 558 grammi
- Dimensioni
- 242x163x19 mm
- Serie
- Libro 6 di 35: Operations Research/Computer Science Interfaces
This book provides successful implementations of metaheuristic methods for neural network training. It is the first book to achieve this objective. Moreover, the basic principles and fundamental ideas given in the book will allow the readers to create successful training methods on their own. Overall, the book's aim is to provide a broad coverage of the concepts, methods, and tools of the important area of ANNs within the realm of continuous optimization.
"Riassunto" può appartenere a un’altra edizione di questo titolo.
Recensione
From the reviews:
"The strength of the book is its clear motivation to bring a new breath from metaheuristics into training of neural networks and integrate both sub-disciplines for the purpose of better exploitation of artificial intelligence approaches. ... The most benefiting reader of this book will perhaps be those who research on modelling data with ANN faced with difficulty of robust mapping with classical training algorithms." (S. Gazioglu, Journal of the Operational Research Society, Vol. 58 (12), 2007)
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