中国及各地区教育经济贡献率的软计算

Estimating Contribution of Education to Local Economy of China through Soft Computing

本文提出了一种新的教育经济贡献率的软计算方法,并提出了潜在人力资本(教育)-实际人力资本-经济增长的计算思路。该算法由4个步骤组成:首先,按照科学技术水平对目标系统进行模糊软分类,得到最佳分类数,从而确定了最佳的规则数;其次,根据规则数确定模糊神经网络的结构,建立潜在人力资本(教育)到实际人力资本的模糊映射,即"一次滤波",得到潜在人力资本(教育)对实际人力资本的贡献率αk;第三,建立实际人力资本到经济增长的模糊映射,即"二次滤波",得到实际人力资本对经济增长的贡献率αk′;第四,计算教育对经济的贡献率ECREk=αk×αk′,其中k为按科技水平划分的类别数。最后,用该算法来计算我国2003-2006年教育对经济的贡献率。

In this paper, a new soft computing method of economic contribution rate of education is proposed. The idea is based on the chain of potential human capital（education） -actual human capital -economic growth. The method is consisted of four steps ： The first step is that clusters object system according to the level of science technology and gets the optimal number of cluster, which determines the number of rules. The second step is that the structure of fuzzy neural networks is determined by the number of rules and the fuzzy neural networks FNN1 from potential human capital（ education） to actual human capital is constructed and we obtain actual human capital rate of education αk. The third step is that the fuzzy neural networks FNN2 from actual human capital to economic growth is constructed and we obtain economic contribution rate of actual human capital α′k. The fourth step is that economic contribution rate of education ECREk =αk ×α′kwhere k is the number of clusters according to the level of science technology. At last, use the algorithm to estimate the economic contribution rate of education in China.