Title :
The Research and Application of LS_SVM Based on Particle Swarm Optimization
Author :
Chen, Yongqi ; Zhou, Zhanxin ; Chen, Qijun
Author_Institution :
Tongji Univ., Shanghai
Abstract :
To select parameters is important in the research area of support vector machine. Based on particle swarm optimization, this paper proposes automatic parameters selection for least squares support vector machine (LSSVM). The effect of this proposed method is demonstrated by function regression problem. Besides, an equipment fault classification further illustrates that LSSVM based on particle swarm optimization has better classification ability than LSSVM based genetic algorithm under the same condition.
Keywords :
least squares approximations; particle swarm optimisation; support vector machines; fault classification; function regression problem; least squares; particle swarm optimization; support vector machine; Automation; Control engineering; Genetic algorithms; Genetic mutations; Kernel; Least squares methods; Particle swarm optimization; Pattern recognition; Support vector machine classification; Support vector machines; fault classification; least squares support vector machine; particle swarm optimization;
Conference_Titel :
Automation and Logistics, 2007 IEEE International Conference on
Conference_Location :
Jinan
Print_ISBN :
978-1-4244-1531-1
DOI :
10.1109/ICAL.2007.4338735
