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.