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

机译:一种估算中国教育经济贡献率的软计算新方法

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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 α{sub}k. The third step constructs the fuzzy neural networks FNN2 from education to human capital and obtains human capital contribution rate of education α'{sub}k. The fourth step calculates the economic contribution rate of education ECE{sub}k = α{sub}k × α'{sub}k. At last, this algorithm is applied to obtain the economic contribution rate of education in China.
机译:教育的经济贡献率(ECE)是教育经济学的关键因素。提出了一种教育经济贡献率的软计算方法。该方法包括四个步骤。第一步,根据科学技术水平对目标系统进行模糊软聚类,获得最优的聚类数量,从而确定模糊规则的数量。第二步,构建了从人力资本到经济增长的模糊神经网络FNN1,得到了人力资本的经济贡献率α{sub} k。第三步,构建了从教育到人力资本的模糊神经网络FNN2,得到了教育对人力资本的贡献率α'{sub} k。第四步,计算教育的经济贡献率ECE {sub} k =α{sub} k×α'{sub} k。最后,将该算法应用于中国教育的经济贡献率。

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