SAFETY ASSESSMENT IN POWER SUPPLY ENTERPRISE BASED ON KERNEL PRINCIPAL COMPONENT ANALYSIS AND FAST MULTI-CLASS SUPPORT VECTOR MACHINE

摘要：

According to the requirement for safety of power supply enterprises, a new method based on kernel principal component analysis and support vector machine is introduced in this paper: kernel principal component analysis which extracts the most important factors influencing safety can optimize the parameters of support vector machine. Fast multi-class support vector machine, as the evaluation tool, classifies enterprises safety condition into four groups. The result of experiment shows that the method can reduce the complex of assessment and is more comprehensive. It also improves rapidity and accuracy of traditional SVM model. Furthermore, the safety of power supply enterprises can be improved by the new method.

关键词： Safety assessment Kernel principal component analysis Fast multi-class support vector machine

作者: WEI SUN GUO-ZHEN MA

作者单位: Department of Economy Management, North China Electric Power University, Baoding 071003, Hebei, China

会议类型: 国际会议

会议名称: 2009 International Conference on Machine Learning and Cybernetics(2009机器学习与控制论国际会议)

会议地点: 保定

会议语种:英文

页码: 1214-1218

在线出版日期: 2009-07-12（万方平台首次上网日期，不代表论文的发表时间）