Development Trend Prediction of Chengdu Plain Economic Zone Based on Multiple Linear Regression Grey Correlation Degree

Abstract

Urban agglomeration is the mainstream trend of urban development in the world. It is also the main form of new urbanization in China and an important platform to participate in international competition and cooperation. The pattern of industrial division of labor has basically taken shape in Chengdu Plain Economic Zone, and the industrial cooperation system has been gradually established. However, the phenomenon of industrial isomorphism is still prominent. In the process of promoting coordinated industrial development, there are still some problems such as disunity of understanding, imperfect mechanism, and imperfect environment. The regional economic potential is influenced by too many entities and the dynamic changes of economic structure, and the change ratio is highly nonlinear. In this paper, a MLR-GCD (Multiple Linear Regression Grey Correlation Degree) prediction model for the development trend of Chengdu Plain Economic Zone is proposed. In the decision-making process, MLR (multiple linear regression) method is introduced to construct the GCD (Grey Correlation Degree) of training economic-related data set, and then the GCD is pruned to transform it into standard decision-making data. The experimental results show that compared with other prediction models, the improved model has higher accuracy of regional economic prediction, can quickly and accurately predict the development potential trend of Chengdu Plain Economic Zone, and has important application value.