A soft computing method of economic contribution rate of education: a case of China

  • Authors:

  • Hai-xiang Guo;Ke-jun Zhu;Jin-ling Li;Yan-min Xing

  • Affiliations:

  • School of Management, China University of Geosciences, Wuhan, Hubei, China;School of Management, China University of Geosciences, Wuhan, Hubei, China;School of Management, China University of Geosciences, Wuhan, Hubei, China;School of Management, China University of Geosciences, Wuhan, Hubei, China

  • Venue:
  • ISNN'06 Proceedings of the Third international conference on Advances in Neural Networks - Volume Part III
  • Year:
  • 2006

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Abstract

Economic contribution rate of education is the key factor of education economy. In this paper, a soft computing method of economic contri-bution rate of education is proposed. The method is composed of four steps: The first step is doing fuzzy soft-clustering to object system based on levels of science technology and getting optimal number of clusters, which determines number of fuzzy rules. The second step is that the fuzzy neural networks FNN1 from human capital to economic growth is constructed and we obtain economic contribution rate of human capital αk. The third step is that the fuzzy neural networks FNN2 from education to human capital is constructed and we obtain human capital contribution rate of education α′k. The fourth step is calculating economic contribution rate of education ECEk=αk ×α′k. At last, the economic contribution rate of education of China is obtained.