基于指标关联性的岩体分级集对云算法研究
投稿时间:2019-03-25  修订日期:2020-06-02  点此下载全文
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作者单位E-mail
曹建立 东北大学资源与土木工程学院 caojianli@mail.neu.edu.cn 
韩智勇 东北大学资源与土木工程学院  
任凤玉 东北大学资源与土木工程学院  
谭宝会 东北大学资源与土木工程学院  
基金项目:国家自然科学基金项目(重点项目),,国家重点研发计划项目
中文摘要:岩体质量分类是一个非线性复杂的不确定系统问题,其分类指标参数具有不确定性、模糊性和随机性。在充分考虑岩体质量分级指标关联性的基础之上,建立了以指标距离为基础的信度测度赋权理论,计算得到了各指标的准确权重,降低了实际过程中因指标实测值出现误差或错误而造成评价结果与实际偏差较大的风险。根据集对论对传统云模型进行改进,提出了集对云模型的概念与算法,通过25组样本数据进行模拟分析,发现评价结果与逼近理想解排序法和分形插值法的评价结果相吻合,证明了该算法的可靠性。将模型应用于锡林浩特萤石矿采场岩体质量评价中,预测结果与实际情况相符,表明该算法具有工程实用价值,可运用于地下工程岩体质量分级。同时该算法根据指标信度类别划分函数可判断指标数据的真伪,可为岩体工程参数采集提供理论指导。
中文关键词:岩体分级算法  指标关联性  Jousselme距离  指标信度测度  集对云模型
 
Research on set pair cloud algorithm of rock mass classification based on index relevance
Abstract:Rock mass quality classification is a non-linear and complex uncertain system problem. Its classification index parameters are uncertain, fuzzy and stochastic. On the basis of fully considering the correlation of rock mass quality classification indexes, the reliability measurement weighting theory based on index distance is established, and the accurate weights of each index are calculated, which reduces the risk of large deviation between the evaluation results and the actual results caused by errors or errors in the actual process. According to set pair theory, the traditional cloud model is improved, and the concept and algorithm of set pair cloud model are proposed. Through simulation analysis of 25 sets of sample data, it is found that the evaluation results coincide with those of approximate ideal solution ranking method and fractal interpolation method, which proves the reliability of the algorithm. The model is applied to the evaluation of rock mass quality in Xilinhot fluorite mine. The predicted results are consistent with the actual situation, which shows that the algorithm has practical engineering value and can be applied to the classification of rock mass quality in underground engineering. At the same time, the algorithm can judge the authenticity of the index data according to the classification function of index reliability, which can provide theoretical guidance for rock engineering parameter acquisition.
keywords:Rock mass classification algorithm  index relevance  Jousselme distance  index reliability measure  set pair cloud mode
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