Paper
PSO Algorithm Improvement Based on Particle Tracing Analysis
- Authors:
- Zhongguo Li; Jie Hou; Kai Wang; Qinghua Liu
- Abstract
- Improvement of Particle Swarm Optimization (PSO) algorithm is a significant work. In this paper, a practical method is proposed to instruct this task with recording all particle search positions and tracking the best particle shift process. Firstly, appropriate velocity bounds are obtained with tracking particle velocity components during iterations. Then particle initialization method is modified. Uniform Probability Random Value (UPRV) is substituted with Uniform Distributed Fixed Value (UDFV) to initiate particles. And it concludes a significant performance improvement. Stochasticity of results initialized with UDFV apparently decreases. It also makes PSO better cover with the search space which causes greater probability to obtain the global best. At least 3 particles can be competent for task with UDFV initialization method after analyzing the best particle shift process among all particles. That greatly enhances the algorithm speed. This paper can be a reference for application and improvement of PSO algorithm used in Support Vector Machine (SVM) parameter optimization.
- Keywords
- Support Vector Machine; Vertical load; Road type recognition; Initialization method
- StartPage
- 18
- EndPage
- 24
- Doi