Spatialization of Industrial Structure of Chengdu-Chongqing Economic Circle Based on GBDT
A new method based on machine learning algorithm for the spatialization of industrial structure is presented for the problems that the current method of GDP spatialization has low precision and is complicated.This article takes the Chengdu-Chongqing economic circle as the research area and spatializes the value of each industry into 1 km X 1 km accuracy.Using GBDT and RF algorithms,the output value of industries is predicted based on multi-source data.The results show that:the coefficient of determination of the prediction model based on multi-source data can reach 0.91;the GBDT model performs better than the RF model in terms of performance;the high-value areas of the primary industry in the Chengdu-Chongqing economic circle are concentrated on both sides of the Wujiang,Fujiang,and Tuojiang rivers,while the low value areas are located in the southern plain;the secondary and tertiary industries are concentrated in the two major cities of Chengdu and Chongqing,and there is a phenomenon of polarization.The research results have important guiding significance for promoting the coordinated development of industries in the Chengdu-Chongqing economic circle,building a modern industrial system,and optimizing industrial layout,while also provide a new approach for industrial spatialization research.
machine learningGBDTnight lightspatialization of industrial structureChengdu-Chongqing economic circle
万方数据
维普
