Hardcover. The performance of an algorithm used depends on the GNA. This book focuses on the comparison of optimizers, it defines a stress-outcome approach which can be derived all the classic criteria (median, average, etc.) and other more sophisticated. Source-codes used for the examples are also presented, this allows a reflection on the "superfluous chance," succinctly explaining why and how the stochastic aspect of optimization could be avoided in some cases. The performance of an algorithm used depends on the GNA. This book focuses on the comparison of optimizers, it defines a stress-outcome approach which can be derived all the classic criteria (median, average, etc. ) and other more sophisticated. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

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D�tails bibliographiques

Titre: Guided Randomness in Optimization, Volume 1 (Hardcover)
�diteur: ISTE Ltd and John Wiley & Sons Inc, London
Date de parution: 2015
Langue: anglais
ISBN � 10 chiffres: 1848218052
ISBN � 13 chiffres: 9781848218055
Reliure: Hardcover
�tat de l'article: new

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Synopsis

The performance of an algorithm used depends on the GNA. This book focuses on the comparison of optimizers, it defines a stress-outcome approach which can be derived all the classic criteria (median, average, etc.) and other more sophisticated. Source-codes used for the examples are also presented, this allows a reflection on the "superfluous chance," succinctly explaining why and how the stochastic aspect of optimization could be avoided in some cases.

� propos de l?auteur

Maurice Clerc is recognized as one of the foremost PSO specialists in the world. A former France Telecom Research and Development engineer, he maintains his research activities as a consultant for the XPS (eXtended Particle Swarm) project.

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