원문정보
보안공학연구지원센터(IJSEIA)
International Journal of Software Engineering and Its Applications
Vol.7 No.5
2013.09
pp.45-54
피인용수 : 0건 (자료제공 : 네이버학술정보)
초록
영어
This paper examines the application of a support vector regression (SVR) approach to identifying relationships between land use characteristics and damages caused by natural hazards. Our empirical results show the outperformance of a SVR model over a multiple ordinary least squares (OLS) regression model in terms of the predictive performance. Nonlinear relationships between land use characteristics and damages are revealed by a SVR model.
목차
Abstract
1. Introduction
2. Support Vector Machine for Regression
3. Data Construction
4. Case Study
4.1. Data Pre-processing and Model Requirements Setup
4.2. Empirical Results
4.3. Relationships between Land use Characteristics and Damages
5. Conclusions
Acknowledgements
References
1. Introduction
2. Support Vector Machine for Regression
3. Data Construction
4. Case Study
4.1. Data Pre-processing and Model Requirements Setup
4.2. Empirical Results
4.3. Relationships between Land use Characteristics and Damages
5. Conclusions
Acknowledgements
References
저자정보
참고문헌
자료제공 : 네이버학술정보