Evaluating the Investment Risk of Electrical Project Based on Particle Swarm Optimization with Support Vector Machine Optimized

摘要：

In this paper, we use Particle Swarm Optimization with Support Vector Machine Optimized to evaluate the Investment risk of electrical project. A hybrid intelligent system is applied to Evaluation of electrical equipment, combining Particle Swarm Optimize Algorithm (PSO) and Support Vector Machines (SVM). At first, we can make use of PSO obtaining appropriate parameters in order to improve the general recognizing ability of SVM. And then, these parameters are used to develop classification rules and train SVM. The effectiveness of our methodology was verified by experiments comparing BP neural networks with our approach.

关键词： SVM particle swarm optimization evaluation of electrical equipmentcomponent

作者: Shuliang Liu Zhizhen Yin

作者单位: Institute of Business Administration North China Electric Power University Baoding, China

会议类型: 国际会议

会议名称: 2009 International Conference on Applied Superconductivity and Electromagnetic Devices(应用超导与电磁装置技术国际会议 ASEME 2009)

会议地点: 成都

会议语种:英文

页码: 332-335

在线出版日期: 2009-09-25（万方平台首次上网日期，不代表论文的发表时间）