基于位移和松弛深度的岩体参数概率反分析方法

doi:10.13722/j.cnki.jrme.2019.0003

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Abstract 鉴于目前工程中含多目标变量多参数输出的概率反分析方法匮乏，在改进多输出支持向量机算法(MSVM)的基础上，建立基于贝叶斯理论(Bayes)的概率反分析方法(B-MSVM方法)。该方法通过改进支持向量机算法形成多个岩体参数与多目标变量之间的映射关系，以分步开挖引起的典型测点的松弛深度和表层变形监测信息为输入，以边坡岩体多个力学参数为待反分析输出，通过选择合适的核函数在改进的支持向量机算法中运算，获得多次开挖条件下待反分析参数的取值及其不确定性动态表征。应用该方法对白鹤滩水电站坝基边坡的力学参数进行反分析，得到10个非相关参数的取值及其不确定性分布，用反分析的参数值计算相应开挖步下边坡典型测点的位移和松弛深度，并与实测值进行对比，结果表明该方法的正确性，并初步讨论本方法在相关参数反分析计算中的应用思路。研究成果为岩土工程参数概率反分析方法的建立提供了思路，具有重要的理论意义和工程实用价值。

Key words：岩石力学白鹤滩水电站岩质边坡松弛深度支持向量机贝叶斯理论概率反分析

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	Articles by authors
	SUN Qiancheng1
	2
	LI Shaojun2
	ZHAO Hongbo3
	ZHENG Minzong2
	YANG Zhiyue4

Cite this article:

SUN Qiancheng1,2,LI Shaojun2, et al. Probabilistic back analysis of rock mechanical parameters based on displacement and relaxation depth[J]. , 2019, 38(9): 1884-1894.

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http://www.rockmech.org/EN/10.13722/j.cnki.jrme.2019.0003 OR http://www.rockmech.org/EN/Y2019/V38/I9/1884

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