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Self-Organizing Migrating Algorithm: Methodology and Implementation: Studies in Computational Intelligence, cartea 626

Editat de Donald Davendra, Ivan Zelinka
en Limba Engleză Hardback – 12 feb 2016
This book brings together the current stateof-the-art research in Self Organizing Migrating Algorithm (SOMA) as a novelpopulation-based evolutionary algorithm, modeled on the predator-preyrelationship, by its leading practitioners. 
As the first ever book on SOMA, this book isgeared towards graduate students, academics and researchers, who are looking fora good optimization algorithm for their applications. This book presents themethodology of SOMA, covering both the real and discrete domains, and itsvarious implementations in different research areas. The easy-to-follow andimplement methodology used in the book will make it easier for a reader toimplement, modify and utilize SOMA.
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Specificații

ISBN-13: 9783319281599
ISBN-10: 3319281593
Pagini: 450
Ilustrații: XVIII, 289 p. 128 illus., 87 illus. in color.
Dimensiuni: 155 x 235 x 19 mm
Greutate: 0.61 kg
Ediția:1st ed. 2016
Editura: Springer International Publishing
Colecția Springer
Seria Studies in Computational Intelligence

Locul publicării:Cham, Switzerland

Public țintă

Research

Cuprins

PartI. Theory.- PartII. Applications.

Textul de pe ultima copertă

This book brings together the current stateof-the-art research in Self Organizing Migrating Algorithm (SOMA) as a novelpopulation-based evolutionary algorithm, modeled on the predator-preyrelationship, by its leading practitioners. 
As the first ever book on SOMA, this book isgeared towards graduate students, academics and researchers, who are looking fora good optimization algorithm for their applications. This book presents themethodology of SOMA, covering both the real and discrete domains, and itsvarious implementations in different research areas. The easy-to-follow andimplement methodology used in the book will make it easier for a reader toimplement, modify and utilize SOMA.  

Caracteristici

The originators and pioneers of the Self-Organizing Migrating Algorithm SOMA present the theory and application domain of the algorithm in a concise and detailed format Presents the SOMA methodology and framework in an integrated way to make it accessible to a number of audiences Divided into a theory and applications part Includes supplementary material: sn.pub/extras