基于MCS-TOPSIS耦合模型的岩体质量分类研究

发布时间：2018-01-09 22:26

  本文关键词：基于MCS-TOPSIS耦合模型的岩体质量分类研究　出处：《岩石力学与工程学报》2017年05期 　论文类型：期刊论文

  更多相关文章： 岩石力学 蒙特卡洛模拟 逼近理想解排序法 不确定性 博弈论 岩体质量分类

【摘要】：岩体质量分类是各类岩土工程实践问题的基础,由于岩体指标参数的模糊性和随机性,故岩体质量分类表现出不确定性,而现有分类模型则忽略了这种参数不确定性对分类结果造成的影响。考虑到分类指标参数的不确定性,在岩体质量分类问题中引入概率描述的可靠度分析方法,提出一种蒙特卡洛模拟(Monte Carlo simulation,简称MCS)和逼近理想解排序法(technique for order preference by similarity to ideal solution,简称TOPSIS)耦合模型。该模型由两部分组成:通过博弈论赋权方法获取分类体系中指标的权重,并结合TOPSIS模型来建立可靠度分析中的极限状态方程;基于MCS方法由TOPSIS模型构建的极限状态方程进行随机的不确定性分析,并通过概率函数给出最终的分类结果。通过25组测试样本对基于博弈论组合赋权的TOPSIS模型进行测试,结果显示该模型的误判率为0,表明MCS-TOPSIS模型中确定性分析的合理性。最后通过Matlab语言编制计算程序,分别由确定性分析和不确定性分析的角度来探讨水布垭地下洞室厂房围岩质量分类。研究结果表明:采用MCS-TOPSIS模型进行岩体质量分类是可行的,该模型具有较高的准确度且易于实现,具有一定的工程应用价值。该研究为岩体质量分类提供了一种新思路。
[Abstract]:Rock mass quality classification is the basis of various geotechnical engineering practice problems. Because of the fuzzy and randomness of rock mass index parameters, rock mass quality classification shows uncertainty. However, the existing classification models ignore the influence of this parameter uncertainty on the classification results. Considering the uncertainty of the classification index parameters, the reliability analysis method of probability description is introduced into the rock mass quality classification problem. A Monte Carlo simulation is proposed for Monte Carlo simulation. MCSs and approximate ideal solution sort method (MCSs). Technique for order preference by similarity to ideal solution. The model consists of two parts: the weight of indicators in the classification system is obtained by game theory weighting method. The limit state equation in reliability analysis is established with TOPSIS model. Based on the MCS method, the limit state equation constructed by TOPSIS model is used for stochastic uncertainty analysis. The final classification results are given by probability function. The TOPSIS model based on game theory combination weight is tested by 25 groups of test samples. The result shows that the error rate of the model is 0. It shows the rationality of deterministic analysis in MCS-TOPSIS model. Finally, the calculation program is compiled by Matlab language. The quality classification of surrounding rock of underground cavern workshop of Shuibuya is discussed by deterministic analysis and uncertainty analysis respectively. The results show that:. It is feasible to use MCS-TOPSIS model to classify rock mass quality. The model is of high accuracy, easy to realize and has certain engineering application value. This study provides a new way for classification of rock mass quality.
【作者单位】： 成都理工大学地质灾害防治与地质环境保护国家重点实验室;
【基金】：国家重点基础研究计划(973)项目(2013CB733202) 国家自然科学基金面上项目(41672282) 四川省青年科技创新研究团队(2015TD0030)~~
【分类号】：TU45
【正文快照】： 分类问题是岩土工程领域中常见的一类课题,如岩体质量分类、岩爆倾向分类、边坡危险性分类等。除从力学和试验角度对这类问题进行研究外,从数学上的多准则综合评价对这类问题进行的研究也逐渐引起了一些研究人员的兴趣[1-3]。尤其是得益于系统工程学科的发展,人们逐渐开始以系，

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