Research on General Fuzzy Min-Max Neural Network and Its Application
Pan Jun-qu · Jisuanji gongcheng · 2008
By analyzing the basic principles of General Fuzzy Min-Max(GFMM) neural network and the accuracy and high performance of fuzzy computation for information intelligent processing, the GFMM neural network is applied to the corporation’s credit rating. With genuine inputs of fuzzy realized, the quantitative inaccuracy of standards of evaluating corporations is alleviated to a large degree. Through credit rating towards companies, it is proved that the algorithm can classify companies availably at a high speed. A new project to credit rating is proposed.