Abstract

This paper is to present a spatial convergence SV model to evaluate economic growth. The spatial lag model considers spatial interaction in terms of dependent variables. By the comparison mean prediction error of the GDP of China from 2005 to 2009 among spatial convergence support vector model, RBF neural networks and BP neural networks, we can indicate that the mean prediction error of the GDP of China from 2005 to 2009 of spatial convergence support vector model is smaller than that of RBF neural networks or BP neural networks. Thus, spatial convergence support vector model is the effective method for economic growth evaluation.

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