Title :
An improved particle swarm optimization algorithm
Author :
Ji, Weidong ; Wang, Keqi
Author_Institution :
Coll. of Mechnical & Electr. Eng., Northeast Forestry Univ., Harbin, China
Abstract :
According to the particle swarm optimization algorithm (PSO) exist precocious and local convergence problem, Put forward a kind of improved particle swarm optimization algorithm, the gradient descent method (BP algorithm) as a particle swarm operator embedded in particle swarm algorithm, By static function approximation to test of the improvement of the particle swarm optimization algorithm, results show that the improved algorithm not only increased global optimization ability, but also avoid the immature convergence problem.
Keywords :
convergence of numerical methods; function approximation; gradient methods; particle swarm optimisation; BP algorithm; PSO; global optimization ability; gradient descent method; immature convergence problem avoidance; improved particle swarm optimization algorithm; local convergence problem; precocious convergence problem; static function approximation; Approximation algorithms; Approximation methods; Testing; Neural Networks; particle swarm optimization; premature;
Conference_Titel :
Computer Science and Network Technology (ICCSNT), 2011 International Conference on
Conference_Location :
Harbin
Print_ISBN :
978-1-4577-1586-0
DOI :
10.1109/ICCSNT.2011.6182027
