Proceedings of the Advances in Materials, Machinery, Electrical Engineering (AMMEE 2017)

Principal Component Analysis (PCA) in Smart Growth Theory

Authors
Qingqing Zhang
Corresponding Author
Qingqing Zhang
Available Online June 2017.
DOI
https://doi.org/10.2991/ammee-17.2017.96How to use a DOI?
Keywords
Smart growth index, Principal Component Analysis.
Abstract
Today, smart growth theory is playing an important role in urban development. In order to help implementing smart growth theories into city design around the world, we select Bendigo in Australia and Galway in Ireland as the objects of study. We define a smart growth index to evaluate the success of the smart growth of a city. The higher the index is, the higher the level of urban smart growth will be. To build an evaluation system, we select 10 indicators of 6 similar mid-sized cities in Australia and Ireland respectively according to ten principles for smart growth and three E's. To eliminate the correlation among different factors, we use Principal Component Analysis to calculate the principal components of collected data and their contribution rate, then linearly combine the value of them to get smart growth function. Put the indicators 'data of Bendigo and Galway into the smart growth function to calculate smart growth index. We find that Bendigo's smart growth index is higher, but it is lower than the average level in selected cities of Australia.
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Proceedings
Advances in Materials, Machinery, Electrical Engineering (AMMEE 2017)
Part of series
Advances in Engineering Research
Publication Date
June 2017
ISBN
978-94-6252-350-0
ISSN
2352-5401
DOI
https://doi.org/10.2991/ammee-17.2017.96How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Qingqing Zhang
PY  - 2017/06
DA  - 2017/06
TI  - Principal Component Analysis (PCA) in Smart Growth Theory
BT  - Advances in Materials, Machinery, Electrical Engineering (AMMEE 2017)
PB  - Atlantis Press
SN  - 2352-5401
UR  - https://doi.org/10.2991/ammee-17.2017.96
DO  - https://doi.org/10.2991/ammee-17.2017.96
ID  - Zhang2017/06
ER  -