Analysis of Influencing Factors of Urban Floating Population by Clustering Algorithms

Abstract

The advancement of the economy and society has driven the increase of the urban floating population, and its analysis plays an important role in urban development. In this paper, ten influencing factors including gross domestic product (GDP) and gross industrial output value were selected to analyze the status of the floating population in ten cities such as Chengdu and Tianjin in 2010 and 2020. Two irrelevant factors were eliminated by the Pearson correlation coefficient, and the remaining eight factors were used to cluster different urban categories by an improved K-means method. The results showed that from 2010 to 2020, the increase of the floating population in Chengdu and Xi 'an was more than 100%, indicating that cities with higher GDP had a stronger ability to absorb the floating population, while high housing prices did not facilitate such absorption. These analysis results provide some references for further research on the status of the urban floating population, which can be applied in actual urban population management.