Ground Collapse Prediction of Mined-Out Area Based on EMD and WLS-SVM
详细信息
- 责任者：Nai Lei (College of Construction and Engineering ; Jilin University ; Changchun 130026 ; China) ; Peng Wen
- 刊名：Journal of Jilin University
- 出版年：2011
- 卷期：41(3)
- 关键词：采空区 ; mined-out section ; 地面沉降 ; land subsidence ; 支持向量机 ; support vector machine
- 页码：p.799-804
- 图表：7 illus., 3 tables, 9 refs.
- 分类号：1800
- issnNo：ISSN1671-5888
- isbnNo：CN22-1343/P
摘要
According to the characteristic of the road collapse data in mined-out area, a method based on empirical mode decomposition (EMD) and weighted least squares support vector machines (WLS-SVM) has been put forward to forecast the ground subsidence and applied into the coal-mining-induced collapse prediction of Changping high way in Jilin Province. Comparing the measured data in situ and the predicted data by WLS-SVM and BP neural network, the result shows that the suggested method has relatively high forecast accuracy and can be applied widely.