Title :
An Enhanced Culture-Based Particle Swarm Optimization Algorithm
Author :
Xu, Yufa ; Liu, Xiang
Author_Institution :
Electr. Eng. Sch., Shanghai Dianji Univ., Shanghai, China
Abstract :
This paper proposes an Enhanced Culture-Based Particle Swarm Optimization algorithm (ECPSO). In this mixed algorithm, Particle Swarm Optimization algorithm (PSO) is used in the Population Space of Cultural Frame and the update formula of the velocity of PSO algorithm is modified. Then this paper redesigns the knowledge of Believe Space and its update method, and a strategy is proposed which makes the history knowledge guide the update of the situational knowledge. The purpose of all the modify methods in this algorithm is to remain the diversity of the population as well as having a faster convergence velocity. The experimental result indicates that this mixed algorithm can show the effect of culture frame enough and enhance the capability of PSO algorithm efficiently.
Keywords :
convergence; knowledge engineering; particle swarm optimisation; PSO algorithm; believe space; convergence velocity; culture-based particle swarm optimization; knowledge guide; mixed algorithm; population space; update formula; Acceleration; Algorithm design and analysis; Classification algorithms; Convergence; Cultural differences; History; Particle swarm optimization; cultural algorithm; frame; knowledge; particle swarm optimization;
Conference_Titel :
Artificial Intelligence and Computational Intelligence (AICI), 2010 International Conference on
Conference_Location :
Sanya
Print_ISBN :
978-1-4244-8432-4
DOI :
10.1109/AICI.2010.258