2019•Unpublished venueRequires access

Study on Urbanization Level Based on Principal Component and Cluster Analysis‐‐A Case Study of Hunan Province

Xianghua Chu, Da Xiao Gao, Wenjia Mao, Zihao Guo, Yizhen Huang, Li Li

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Abstract

In this paper, four first-level indicators are selected, and a total of 24 second-level indicators are used to construct an evaluation index system for urbanization development level. Using 14 cities and prefectures in Hunan Province as samples, principal component analysis and cluster analysis were used to analyze and evaluate their urbanization development level. It was found that Changsha had the highest level of urbanization development, and Shaoyang City and Xiangxi Prefecture were the worst. Then we gave explanations and suggestions for adjustment and development.

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What this paper is about

In this paper, four first-level indicators are selected, and a total of 24 second-level indicators are used to construct an evaluation index system for urbanization development level. Using 14 cities and prefectures in Hunan Province as samples, principal component analysis and cluster analysis were used to analyze and evaluate their urbanization development level. It was found that Changsha had the highest level of urbanization development, and Shaoyang City and Xiangxi Prefecture were the worst. Then we gave explanations and suggestions for adjustment and development.

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Available abstract

In this paper, four first-level indicators are selected, and a total of 24 second-level indicators are used to construct an evaluation index system for urbanization development level. Using 14 cities and prefectures in Hunan Province as samples, principal component analysis and cluster analysis were used to analyze and evaluate their urbanization development level. It was found that Changsha had the highest level of urbanization development, and Shaoyang City and Xiangxi Prefecture were the worst. Then we gave explanations and suggestions for adjustment and development.

Key concepts: Urbanization, Principal component analysis, Cluster (spacecraft), Geography, Index (typography), Regional science, Economic growth, Computer science

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