Earticle

초록

영어

Due to the normal forecasting methods for subgrade settlement using observation data have different applicability and disadvantages, The Combined forecasting model is put forward based on support vector machine (SVM) and real-coded quantum evolutionary algorithm (RQEA) in this paper. Its core is that, according to the basic settlement law of subgrade and characteristics of settlement curve, the growth curve which has S-type characteristic are chosen as single forecasting model, then support vector machine is used to combine the predicting results of each single forecasting model, at the same time, RQEA is adopted to optimize support vector machine parameter to improve the SVM’s performance. The analytical result of engineering practice indicates that the proposed combined forecasting model of subgrade settlement base on SVM and RQEA can not only improve the predicting accuracy, but also reduce the predicting risk, and can meet engineering demand.

목차

Abstract
 1. Introduction
 2. Support Vector Machine (SVM)
 3. Real-coded Quantum Evolutionary Algorithm (RQEA)
 4. Combined Forecasting Model based on SVM and RQEA
  4.1. The Selection of Single Forecasting Model
  4.2. Optimizing SVM Parameters based on RQEA
  4.3. Structure of Combined Forecasting Model
 5. The Application of Combined Forecasting Model
 6. Conclusion
 References

키워드

저자

• Gao Hui [ School of Electrical and Information Engineering, Heilongjiang Institute of Technology, Harbin, Heilongjiang, China 150050 ]
• Huang Jun [ Faculty of Geosciences and Environmental Engineering, Southwest Jiaotong University, Chengdu, Sichuan, China, Chengdu Donglu Traffic Science and Technology Co.,Ltd. Chengdu, Sichuan, China 610031 ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Hybrid Information Technology

• 간기

  격월간

• pISSN

  1738-9968

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605