원문정보
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
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