Smart Growth Prediction Based on Support Vector Regression
Feiyang Li, Wenjie Chen, Weijian Chen, Nian Cai
Available Online March 2017.
- 10.2991/msam-17.2017.34How to use a DOI?
- smart growth; principle component analysis; support vector regression
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.
- © 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 - 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 -