Classification Technology by Least Squares Support Vector Machine Trained by Chaos Particle Swarm Optimization

摘要：

In the paper, least squares support vector machine trained by chaos particle swarm optimization (CPSOLSSVM) is applied in the classification. Chaos particle swarm optimization algorithm is introduced to select the suitable training parameters of least squares support vector machine. That is because chaos particle swarm optimization algorithm can avoid being trapped in local optimum and gaining the global optimum quickly in the process of search by combining particle swarm optimization with chaos queues. The experimental results demonstrate that least squares support vector machine trained by chaos particle swarm optimization is best classification results in the three classification algorithms.

关键词： least squares classification technology particle swarm optimization chaos

作者: Yanhong Li Taihui Liu

作者单位: Mathematical College Beihua University Jilin 132013, China Computer College Beihua University Jilin 132013, China

会议类型: 国际会议

会议名称: 2010 3rd International Conference on Environmental and Computer Science(2010年第三届环境与计算机科学国际会议 ICECS 2010)

会议地点: 昆明

会议语种:英文

页码: 33-35

在线出版日期: 2010-10-17（万方平台首次上网日期，不代表论文的发表时间）