Abstract

The scientific planning of urban future space layout improves the quality of the regional economy for the city's future development and has important guiding significance. Taking Shanghai as an example, this paper first quantifies the regional industrial cluster and regional economy, then constructs the artificial neural network-radial basis function (ANN-RBF) algorithm and sets the algorithm test index. Based on data collection, RBF is used for contribution analysis to explore the impact of regional industrial clusters on regional economic indicators in Shanghai, China. The results show that the ratio of foreign investment (11.4%), the percentage of the tertiary industry's added value to the secondary industry's (10%) to the regional economy of Shanghai, China is more prominent than the other indicators. The scientific and technological achievements, energy consumption per unit of GDP, and electricity consumption accounted relatively small. This paper's significance is conducive to analyzing the correlation between regional economic and industrial cluster indicators in Shanghai, China.

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