Smart Growth Prediction Based on Support Vector Regression

DOI

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.

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)

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  - Proceedings of the 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  - 10.2991/msam-17.2017.34
ID  - Li2017/03
ER  -