Proceedings of the 2017 2nd International Conference on Modelling, Simulation and Applied Mathematics (MSAM2017)

Smart Growth Prediction Based on Support Vector Regression

Authors
Feiyang Li, Wenjie Chen, Weijian Chen, Nian Cai
Corresponding Author
Feiyang Li
Available Online March 2017.
DOI
https://doi.org/10.2991/msam-17.2017.34How to use a DOI?
Keywords
smart growth; principle component analysis; support vector regression
Abstract
Smart growth is a technique to improve the quality of development for a city. To effectively measure the degree of smart growth, an evaluation model is proposed based on principle component analysis (PCA) in this report. We use support vector Regression (SVR) to predict the components of smart growth and measure the degree of smart growth in the future. Our experimental results indicate that the proposed model is feasible to measure the degree of smart growth of a city and predict the trends of smart growth.
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Proceedings
2017 2nd International Conference on Modelling, Simulation and Applied Mathematics (MSAM2017)
Part of series
Advances in Intelligent Systems Research
Publication Date
March 2017
ISBN
978-94-6252-324-1
ISSN
1951-6851
DOI
https://doi.org/10.2991/msam-17.2017.34How 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  - Feiyang Li
AU  - Wenjie Chen
AU  - Weijian Chen
AU  - Nian Cai
PY  - 2017/03
DA  - 2017/03
TI  - Smart Growth Prediction Based on Support Vector Regression
BT  - 2017 2nd International Conference on Modelling, Simulation and Applied Mathematics (MSAM2017)
PB  - Atlantis Press
SP  - 152
EP  - 155
SN  - 1951-6851
UR  - https://doi.org/10.2991/msam-17.2017.34
DO  - https://doi.org/10.2991/msam-17.2017.34
ID  - Li2017/03
ER  -