The Smart Growth Measurement and Comparison Model Based on the Principal Component Analysis

被引：0
|
作者：
Zhang, Wuyu [1 ]
机构：
[1] North China Elect Power Univ, Sch Elect & Elect Engn, Baoding 071000, Peoples R China
来源：
PROCEEDINGS OF THE 2017 5TH INTERNATIONAL CONFERENCE ON MACHINERY, MATERIALS AND COMPUTING TECHNOLOGY (ICMMCT 2017) | 2017年 / 126卷
关键词：
smart growth; principal component analysis; metric;
D O I：
暂无
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
Smart growth is about helping cities become economically prosperous, socially equitable, and environmentally sustainable place to live. The purpose of this paper is establishing a model to measure and compare the smart growth degree. Principle component analysis is a suitable method since the factors affecting the smart growth degree are complicated. These factors involve ten principles of smart growth and three E's of sustainability. Through selecting the principle components, I can simplify the method of evaluation at most. Then I choose Cleveland in US and Jiayuguan in China as research objects. According the model, I got the scores on each indicators about each cities, also got the final smart growth of each cities.
引用
收藏
页码：362 / 365
页数：4
相关论文
共 50 条
  • [21] Financial Agglomeration Level Domain Western Province Based on Principal Component Analysis Measurement
    Zhang, Hongmei
    Li, Teng
    Meng, Xiangrui
    Wang, Ziyan
    PROCEEDINGS OF THE 7TH ANNUAL MEETING OF RISK ANALYSIS COUNCIL OF CHINA ASSOCIATION FOR DISASTER PREVENTION, 2016, 128 : 558 - 563
  • [22] SELECTION OF COMPONENTS IN PRINCIPAL COMPONENT ANALYSIS - A COMPARISON OF METHODS
    FERRE, L
    COMPUTATIONAL STATISTICS & DATA ANALYSIS, 1995, 19 (06) : 669 - 682
  • [23] A comparison of robust principal component analysis in high dimensions
    Liu, Yun
    Shu, Lianjie
    Li, Yanting
    Tian, Guoliang
    COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION, 2025,
  • [24] Reducing dimensionality in principal component analysis -: A method comparison
    Kánya, Z
    Forgács, E
    Cserháti, T
    Illés, Z
    CHROMATOGRAPHIA, 2006, 63 (3-4) : 129 - 134
  • [25] Polarization Aberration Measurement Method Based on Principal Component Analysis of Differential Aerial Images
    Meng Zejiang
    Li Sikun
    Wang Xiangzhao
    Bu Yang
    Yang Chaoxing
    Dai Fengzhao
    ACTA OPTICA SINICA, 2019, 39 (07)
  • [26] Comparison and Empirical Analysis between Principal Component Analysis and Factor Analysis
    Xu, Lu
    Zhang, Yingying
    PROCEEDINGS OF THE 2013 INTERNATIONAL CONFERENCE ON ADVANCES IN SOCIAL SCIENCE, HUMANITIES, AND MANAGEMENT, 2013, 43 : 750 - 755
  • [27] Reducing Dimensionality in Principal Component Analysis – A Method Comparison
    Z. Kánya
    E. Forgács
    T. Cserháti
    Z. Illés
    Chromatographia, 2006, 63 : 129 - 134
  • [28] Principal Component Analysis of Price Fluctuation in the Smart Grid Electricity Market
    Li, Kun
    Cursio, Joseph D.
    Sun, Yunchuan
    SUSTAINABILITY, 2018, 10 (11):
  • [29] The Research on Broadcast Television User Interest Model Based on Principal Component Analysis
    Wang, Xin
    Yin, FuLian
    Yang, TianRui
    Liu, JianBo
    IEEE 12TH INT CONF UBIQUITOUS INTELLIGENCE & COMP/IEEE 12TH INT CONF ADV & TRUSTED COMP/IEEE 15TH INT CONF SCALABLE COMP & COMMUN/IEEE INT CONF CLOUD & BIG DATA COMP/IEEE INT CONF INTERNET PEOPLE AND ASSOCIATED SYMPOSIA/WORKSHOPS, 2015, : 578 - 581
  • [30] Research on e-Government evaluation model based on the principal component analysis
    Siqing Shan
    Li Wang
    Jing Wang
    Yi Hao
    Fan Hua
    Information Technology and Management, 2011, 12 : 173 - 185
12345