Benefit Evaluating of Pumped Storage Station Based on Rough Set and Support Vector Machine

被引：0

作者：

Sun, Wei ^{[1
]}

Zhang, Xing ^{[1
]}

机构：

[1] N China Elect Power Univ, Dept Econ Management, Baoding 071003, Hebei, Peoples R China

来源：

2008 7TH WORLD CONGRESS ON INTELLIGENT CONTROL AND AUTOMATION, VOLS 1-23 | 2008年

关键词：

pumped storage station; support vector machine; rough set; attribute reduction algorithm;

D O I：

10.1109/WCICA.2008.4593810

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Based on the character and function of pumped storage station, a benefit evaluating indexes system is established. Considering the indexes are considerable, an hybrid model based on rough set (RS) and support vector machine(SVM) is proposed: Rough sets, as a anterior preprocessor of SVM, can find out the kernel factors influencing the safety of power supply enterprise by means of attribute reduction algorithm, and then, using them as the input vectors of SVM, the safety assessment is conducted. Experiment results compared with traditional SVM model show that the accuracy of the RS-SVM model are evidently improved.

引用

页码：5401 / 5405

页数：5