원문정보
보안공학연구지원센터(IJUNESST)
International Journal of u- and e- Service, Science and Technology
Vol.9 No.7
2016.07
pp.101-108
피인용수 : 0건 (자료제공 : 네이버학술정보)
초록
영어
Due to the normal forecasting methods for subgrade settlement using observation data have different applicabilities, and the predicting results has bigger volatility and lower accuracy. In view of the above problems, based on the twin support vector regression tool, the settlement prediction model is established by combining with the measured roadbed settlement data; The related parameters of the prediction model are given and compared with the standard support vector regression machine, the comparison tests show that the twins support vector regression is a new method to predict the settlement of the roadbed, and is superior in forecasting accuracy to the standard support vector regression.
목차
Abstract
1. Introduction
2. Standard Support Vector Regression Machine
3. Twin support Vector Regression Machine
4. Prediction of Subgrade Settlement Model with Double Support Vector Regression Machine
4.1. Prediction of Subgrade Settlement
4.2. Prediction of Roadbed Settlement Based on TSVR
6. Conclusion
Acknowledgments
References
1. Introduction
2. Standard Support Vector Regression Machine
3. Twin support Vector Regression Machine
4. Prediction of Subgrade Settlement Model with Double Support Vector Regression Machine
4.1. Prediction of Subgrade Settlement
4.2. Prediction of Roadbed Settlement Based on TSVR
6. Conclusion
Acknowledgments
References
키워드
저자정보
참고문헌
자료제공 : 네이버학술정보