洞室围岩变形预测的ACA-LSSVM模型及工程应用研究

长江科学院院报 ›› 2009, Vol. 26 ›› Issue (2): 32-35.

洞室围岩变形预测的ACA-LSSVM模型及工程应用研究

徐飞, 徐卫亚, 刘大文, 刘康

出版日期:2009-02-01 发布日期:2012-07-02

ACA-LSSVM for Deformation Forecasting of Cavern Surrounding Rock and Its Application

XU Fei, XU Wei-Ya, LIU Da-Wen, LIU Kang

Online:2009-02-01 Published:2012-07-02

摘要/Abstract

摘要： 现场监测获得的围岩变形信息，从宏观上反映了洞室的力学性态变化。为克服人工神经网络方法的过学习问题，提出了一种新的洞室围岩变形预测模型——进化支持向量机模型。该模型利用蚁群算法来搜索支持向量机的惩罚因子和核函数参数,避免了人为选择参数的盲目性，提高了支持向量机的推广预测能力。应用该非线性智能预测方法,滚动预测围岩变形量,能及时发现异常情况，从而调整和优化施工步序,维护洞室的稳定性。将该方法用于锦屏一级水电站工程洞室变形预测,结果表明,该方法具有科学可靠、实时性的优点,具有广泛的应用前景。

Abstract: The insitu monitoring data of surrounding rock displacements reflect the changing of mechanical situation of a cavern. In order to overcome the excessive learning of ANN, a new method, ACA-LSSVM , is presented to forecast the nonlinear displacements of surrounding rock. An ant colony algorithm is used to choose parameters of support vector machine. It can escape from the blindness of manmade choice and enhances the efficiency and the capability of forecasting. The method can forecast in rolling the surrounding rock displacements on the basis of monitoring data, in order to discover abnormal situation in time, adjust the supporting schemes dynamically and ensure the stability of surrounding rock of the cavern. The engineering case studies indicate that it is scientific and there is an extensive prospect for this real time forecasting.

徐飞, 徐卫亚, 刘大文, 刘康. 洞室围岩变形预测的ACA-LSSVM模型及工程应用研究[J]. 长江科学院院报, 2009, 26(2): 32-35.

XU Fei, XU Wei-Ya, LIU Da-Wen, LIU Kang. ACA-LSSVM for Deformation Forecasting of Cavern Surrounding Rock and Its Application[J]. JOURNAL OF YANGTZE RIVER SCIENTIFIC RESEARCH INSTI, 2009, 26(2): 32-35.