Study on LSSVR Modeling Positioning Based on Particle Swarm Optimization

摘要：

　　Particle Swarm Optimization (PSO) is a new intelligent optimization algorithm and it iteratively searches the parameter space in parallel to optimize.The method is simple and practical,with fewer adjustable parameters which has been widely researched and applied.This paper intends to make PSO to the modeling parameter of the least squares support vector machine (LSSVM),to improve its positioning effect and precision of modeling positioning.

关键词： Particle Swarm Optimization Least Squares Support Vector Machine Modeling Positioning Precision

作者: Xuewen He Wenqian Huang

作者单位: School of Mechanical and Electrical Engineering, Jiangxi University of Science and Technology,Ganzhou, 341000, China

会议类型: 国际会议

会议名称: 2013 3rd International Symposium on Chemical Engineering and Material Properties(2013第三届化学工程和材料性能国际研讨会)(ISCEMP 2013)

会议地点: 三亚

会议语种:英文

页码: 215-218

在线出版日期: 2013-06-22（万方平台首次上网日期，不代表论文的发表时间）