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Based on the characteristics of coal and power pool project, a financing risk assessment 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 financing risk of coal and power pool project by means of attribute reduction algorithm, and then, using them as the input vectors of SVM, the financing risk assessment is conducted. Experiment results compared with traditional SVM model show that the accuracy of the RS-SVM model is evidently improved.
Date of Conference: 14-17 July 2012