A better estimate to the contribution rate of education on economic growth in China from 1999 to 2003

The traditional methods of estimating economic contribution rate of education (ECRE) are based on hard computing such as statistical methods, which ignore both the long-term effect of education and the lagged effect of education on economy growth. This paper proposes the fusion method of neural networks, fuzzy systems and genetic algorithms made in the realm of soft computing to estimate the ECRE. Firstly, a target system (a country or a region) is categorized softly according to the level of Science and Technology (ST the second cluster (developing ST the third cluster (underdeveloped S&T) has an ECRE of 1.49% and contains 18 provinces.

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