| AOSVR在地下厂房围岩变形预测中的应用 |
| |
| 引用本文： | 金长宇,马震岳,张运良.AOSVR在地下厂房围岩变形预测中的应用[J].地下空间与工程学报,2006,2(Z2):1379-1382. |
| |
| 作者姓名： | 金长宇 马震岳 张运良 |
| |
| 作者单位： | 大连理工大学,土木水利学院,辽宁,大连,116024 |
| |
| 摘 要： | 针对目前广泛使用的模糊系统和神经网络预测方法在地下结构围岩变形预测中的缺陷,提出一种精确在线支持向量机(AOSVR)并将其应用到水电站地下厂房开挖过程中顶拱围岩的变形预测.通过与其他预测方法的比较,可以发现精确在线支持向量机有很强的学习能力和很高的预测精度.
|
| 关 键 词： | 水电站地下厂房 围岩变形 预测 |
| 文章编号： | 1673-0836(2006)08-1379-04 |
| 修稿时间： | 2006年9月15日 |
Application of AOSVR on Surrounding Rock Displacement Forecasting of Underground Powerhouse |
| |
| JIN Chang-yu,MA Zhen-yue,ZHANG Yun-liang.Application of AOSVR on Surrounding Rock Displacement Forecasting of Underground Powerhouse[J].Chinese Journal of Underground Space and Engineering,2006,2(Z2):1379-1382. |
| |
| Authors: | JIN Chang-yu MA Zhen-yue ZHANG Yun-liang |
| |
| Abstract: | Because the prediction accuracy of ANN and Fuzzy system algorithm is insufficient for underground powerhouse rock surrounding stability, the method of Accurate Online Support Vector Regression(AOSVR) was applied to study the evolution law for underground powerhouse rock surrounding displacement. Comparison of the forecasting results of ANN and Fuzzy System with the monitoring result for rock surrounding displacement of underground powerhouse show that the learning efficiency and prediction accuracy of AOSVR is superior to ANN and Fuzzy System obviously. |
| |
| Keywords: | AOSVR underground powerhouse AOSVR surrounding rock displacement prediction |
| 本文献已被 万方数据 等数据库收录！ |
