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Probabilistic back analysis based on Bayesian and multi-output support vector machine for a high cut rock slope

文献类型：期刊论文

作者Ru, Zhongliang2; Li, Shaojun1; Zhao, Hongbo2; Sun, Qiancheng1
刊名ENGINEERING GEOLOGY
出版日期2016
卷号203页码:178-190
关键词Rock slope Probabilistic back analysis Bayesian theory Multi-output support vector machine
ISSN号0013-7952
DOI10.1016/j.enggeo.2015.11.004
英文摘要Uncertainty of geomechanical parameters is an important consideration for rock engineering and has a very important influence on safety evaluation, design, and construction. Back analysis is a common method of determining geomechanical parameters but traditional deterministic back analysis cannot allow for consideration of this uncertainty. In this study, a new probabilistic back analysis method is proposed that integrates Bayesian methods and a multi-output support vector machine (B-MSVM). In this B-MSVM back analysis method, Bayesian was used to deal with the uncertainty of geomechanical parameters and a multi-output support vector machine (MSVM) was adopted to build the relationships between displacements and those parameters. The proposed method was applied to a high abutment rock slope at the Longtan hydropower station, China. At Longtan, the uncertainty of the two types of geomechanical parameters, Young's modulus and lateral pressure coefficients of in situ stress, were modeled as random variables. Based on the parameters identified by probabilistic back analysis, the computed displacements agreed closely with the measured displacement data monitored in the field. The result showed that B-MSVM presented the uncertainty of the geomechanical parameters reasonably. Further study indicated that the performance of B-MSVM could be improved greatly by updating field monitoring information regularly. The proposed method provides a significant new approach for probabilistic back analysis and contributes to the determination of realistic geomechanical parameters. (C) 2015 Elsevier B.V. All rights reserved.
WOS研究方向Engineering ; Geology
语种英语
WOS记录号WOS:000372688600016
出版者ELSEVIER SCIENCE BV
源URL[http://119.78.100.198/handle/2S6PX9GI/3845]  
专题岩土力学所知识全产出_期刊论文
国家重点实验室知识产出_期刊论文
作者单位1.Chinese Acad Sci, Inst Rock & Soil Mech, State Key Lab Geomech & Geotech Engn ;
2.Henan Polytech Univ, Sch Civil Engn
推荐引用方式
GB/T 7714		 Ru, Zhongliang,Li, Shaojun,Zhao, Hongbo,et al. Probabilistic back analysis based on Bayesian and multi-output support vector machine for a high cut rock slope[J]. ENGINEERING GEOLOGY,2016,203:178-190.
APA Ru, Zhongliang,Li, Shaojun,Zhao, Hongbo,&Sun, Qiancheng.(2016).Probabilistic back analysis based on Bayesian and multi-output support vector machine for a high cut rock slope.ENGINEERING GEOLOGY,203,178-190.
MLA Ru, Zhongliang,et al."Probabilistic back analysis based on Bayesian and multi-output support vector machine for a high cut rock slope".ENGINEERING GEOLOGY 203(2016):178-190.

入库方式： OAI收割

来源：武汉岩土力学研究所

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