Earticle

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

키워드

저자

• Gao Hui [ School of Electrical and Information Engineering, Heilongjiang Institute of Technology, Harbin, Heilongjiang, China ]
• Song Qi-chao [ School of Electrical and Information Engineering, Heilongjiang Institute of Technology, Harbin, Heilongjiang, China ]
• Huang Jun [ Faculty of Geosciences and Environmental Engineering, Southwest Jiaotong University, Chengdu, Sichuan, China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of u- and e- Service, Science and Technology

• 간기

  격월간

• pISSN

  2005-4246

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605