A new method of soft computing to estimate the economic contribution rate of education in China

作者：Guo Haixiang^*; Diao Fengqin; Zhu Kejun; Li Jinling; Xing Yanmin

来源：Applied Soft Computing, 2008, 8(1): 499-506.

DOI：10.1016/j.asoc.2007.02.011

• soft computing
• fuzzy neural networks
• the economic contribution rate of education

Economic contribution rate of education (ECE) is the key factor of education economics. In this paper, a soft computing method of economic contribution rate of education is proposed. The method is composed of four steps. The first step does fuzzy soft-clustering to object system based on levels of science and technology and obtains the optimal number of clusters, which determines the number of fuzzy rules. The second step constructs the fuzzy neural networks FNN1 from human capital to economic growth and obtains economic contribution rate of human capital alpha(k). The third step constructs the fuzzy neural networks FNN2 from education to human capital and obtains human capital contribution rate of education alpha(k)'. The fourth step calculates the economic contribution rate of education ECEk = alpha(k) x alpha(k)'. At last, this algorithm is applied to obtain the economic contribution rate of education in China.

• 出版日期2008-1
• 单位中国地质大学（北京）