Multi-dimensional analysis of urban shrinkage problem in Liaoning Province based on multi-index system, grey correlation analysis and BP neural network with particle swarm optimization

Abstract

The rapid development of urbanization in modern China is accompanied by the increasingly serious problem of urban shrinkage. To provide an effective analytical model for the urban shrinkage problem, this paper takes Liaoning Province, which is one of the typical provinces with a serious urban shrinkage issue in China, as an example. Based on the data from 30 cities in Liaoning Province in recent years, this paper constructs a multi-index system for shrinking cities to evaluate and classify the shrinkage degree of 30 cities. The grey relation analysis model is also used to quantitatively analyze the influence of various factors on the shrinking city population, while the back-propagation neural network algorithm model optimized with particle swarm optimization is also applied to predict the development trend of shrinking cities. The results present the shrinking properties of 30 cities and correlations between different city indicators, as well as the predictive development trend of the shrinking city.