Particle swarm optimization / / Edited by Alex Lazinica.

Particle swarm optimization (PSO) is a population based stochastic optimization technique influenced by the social behavior of bird flocking or fish schooling.PSO shares many similarities with evolutionary computation techniques such as Genetic Algorithms (GA). The system is initialized with a popul...

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Bibliographic Details
TeilnehmendeR:
Place / Publishing House:Rijeka, Croatia : : InTech,, [2009]
©2009
Year of Publication:2009
Language:English
Physical Description:1 online resource (488 pages) :; illustrations
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245 0 0 |a Particle swarm optimization /  |c Edited by Alex Lazinica. 
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264 4 |c ©2009 
300 |a 1 online resource (488 pages) :  |b illustrations 
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588 |a Description based on: online resource; title from PDF information screen (Intech, viewed October 7, 2022). 
504 |a Includes bibliographical references. 
520 |a Particle swarm optimization (PSO) is a population based stochastic optimization technique influenced by the social behavior of bird flocking or fish schooling.PSO shares many similarities with evolutionary computation techniques such as Genetic Algorithms (GA). The system is initialized with a population of random solutions and searches for optima by updating generations. However, unlike GA, PSO has no evolution operators such as crossover and mutation. In PSO, the potential solutions, called particles, fly through the problem space by following the current optimum particles. This book represents the contributions of the top researchers in this field and will serve as a valuable tool for professionals in this interdisciplinary field. 
546 |a English 
650 0 |a Artificial intelligence. 
650 0 |a Swarm intelligence. 
653 |a Computer architecture & logic design 
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700 1 |a Lazinica, Alex,  |e editor. 
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