Proceedings of the 2017 2nd International Conference on Materials Science, Machinery and Energy Engineering (MSMEE 2017)

Study on Smart Growth Metric Model

Authors
Xiaolong Xu
Corresponding Author
Xiaolong Xu
Available Online May 2017.
DOI
10.2991/msmee-17.2017.114How to use a DOI?
Keywords
Gray Relational Analysis, Gray Forecasting Model, Smart Growth
Abstract

We establish the metric model, Smart Growth Metric (SGM). It is divided into Economic Status Metric system, Social Status Metric system and Ecological Environment Metric system. Each system consists of several indicators. Based on the ten principles of smart growth and 3 E's, we select the indicators, such as urban per capita road area and the degree of land mixing. We make some adjustments to these indicators to evaluate the economy, society and environment. By Gray Relational Analysis, we assign weights to each indicator in their system. Since different cities are at different levels, we give the economy, society and environment different weight combinations. These combinations apply to underdeveloped cities, developing cities and developed cities, respectively.

Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Download article (PDF)

Volume Title
Proceedings of the 2017 2nd International Conference on Materials Science, Machinery and Energy Engineering (MSMEE 2017)
Series
Advances in Engineering Research
Publication Date
May 2017
ISBN
978-94-6252-346-3
ISSN
2352-5401
DOI
10.2991/msmee-17.2017.114How to use a DOI?
Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Xiaolong Xu
PY  - 2017/05
DA  - 2017/05
TI  - Study on Smart Growth Metric Model
BT  - Proceedings of the 2017 2nd International Conference on Materials Science, Machinery and Energy Engineering (MSMEE 2017)
PB  - Atlantis Press
SP  - 583
EP  - 586
SN  - 2352-5401
UR  - https://doi.org/10.2991/msmee-17.2017.114
DO  - 10.2991/msmee-17.2017.114
ID  - Xu2017/05
ER  -