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Kategorie szczegółowe BISAC
 Advances in Evolutionary Computing: Theory and Applications Ghosh, Ashish 9783540433309 Springer
Advances in Evolutionary Computing: Theory and Applications

Ghosh, Ashish

The term evolutionary computing (EC) refers to the study of the foundations and applications of certain heuristic techniques based on the principles of natural evolution, and thus the aim when designing evolutionary algorithms (EAs) is to mimic some of the processes taking place in natural evolution.

Many researchers around the world have been developing EC methodologies for designing intelligent decision-making systems for a variety of real-world problems. This book provides a collection of 40 articles, written by leading experts in the field, containing new material on both the...

The term evolutionary computing (EC) refers to the study of the foundations and applications of certain heuristic techniques based on the principle...

cena: 603,81
 Advances in Evolutionary Computing: Theory and Applications Ghosh, Ashish 9783642623868 Springer
Advances in Evolutionary Computing: Theory and Applications

Ghosh, Ashish
The term evolutionary computing refers to the study of the foundations and applications of certain heuristic techniques based on the principles of natural evolution; thus the aim of designing evolutionary algorithms (EAs) is to mimic some of the processes taking place in natural evolution. These algo- rithms are classified into three main categories, depending more on historical development than on major functional techniques. In fact, their biological basis is essentially the same. Hence EC = GA uGP u ES uEP EC = Evolutionary Computing GA = Genetic Algorithms, GP = Genetic Programming ES =...
The term evolutionary computing refers to the study of the foundations and applications of certain heuristic techniques based on the principles of nat...
cena: 603,81
 Massively Parallel Evolutionary Computation on Gpgpus Tsutsui, Shigeyoshi 9783662513453 Springer
Massively Parallel Evolutionary Computation on Gpgpus

Tsutsui, Shigeyoshi

Evolutionary algorithms (EAs) are metaheuristics that learn from natural collective behavior and are applied to solve optimization problems in domains such as scheduling, engineering, bioinformatics, and finance. Such applications demand acceptable solutions with high-speed execution using finite computational resources. Therefore, there have been many attempts to develop platforms for running parallel EAs using multicore machines, massively parallel cluster machines, or grid computing environments. Recent advances in general-purpose computing on graphics processing units (GPGPU) have...

Evolutionary algorithms (EAs) are metaheuristics that learn from natural collective behavior and are applied to solve optimization problems in doma...

cena: 201,24


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