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Particle Swarm Optimization and Intelligence: Advances and Applications by Konstantinos E. Parsopoulos, Michael N. Vrahatis
Particle Swarm Optimization and Intelligence: Advances and Applications Konstantinos E. Parsopoulos, Michael N. Vrahatis ebook
Format: pdf
Page: 329
Publisher: Information Science Publishing
ISBN: 1615206663, 9781615206667
In many filtering applications −3 dB frequency has become a recognizable parameter for defining the cut-off frequency (the frequency at which the magnitude attains an absolute value of 0.5). International Journal of Intelligent Information Technology Application (IJIITA), ISSN 1999-2459 (Print) Journal of Environmental Technology and Engineering, ISSN Vehicle manufacturing processes. Particle Swarm Optimization and Intelligence: Advances and Applications examines recent nimble improvement algorithms proven as rattling economical in applications from different subject and subject fields. ICCSA 2013 is the next event in the series of highly successful International Conferences on Computational Science and Its Applications, previously held in Salvador de Bahia, Brazil (2012), Santander, Spain (2011), Fukuoka, .. Evolutionary algorithms stand upon some common characteristics like stochastic, adaptive, and learning in order to produce intelligent optimization schemes. Amazon.com: Multi-Objective Optimization Using Evolutionary. RGA, PSO, and DE have also been adopted for the sake of comparison. This special issue will therefore focus on recent advances in swarm intelligence applications in power engineering. The application of evolutionary. IGI Global: Particle Swarm Optimization and Intelligence: Advances. Computational Intelligence: Neural Networks Evolutionary Learning & Genetic Algorithms Granular computing & Rough sets.