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基于偏序集的采空区塌陷危险性评价研究
引用本文:黄亮,王会敏,岳立柱,金珊. 基于偏序集的采空区塌陷危险性评价研究[J]. 中国安全生产科学技术, 2019, 15(4): 134-140. DOI: 10.11731/j.issn.1673-193x.2019.04.021
作者姓名:黄亮  王会敏  岳立柱  金珊
作者单位:(1.辽宁工程技术大学 矿业学院,辽宁 阜新 123000;2. 东北大学 资源与土木工程学院, 辽宁 沈阳 110819;3. 辽宁工程技术大学 公共管理与法学院,阜新转型创新发展研究院, 辽宁 阜新 123000)
基金项目:基金项目: 国家自然科学基金委员会与中国民用航空局联合项目(U1733117);中央高校基本科研业务费项目(ZYGX2018003)
摘    要:针对采空区塌陷危险性评价方法中的赋权争议问题,基于偏序集理论提出偏序集评价模型。首先阐明评价指标并确定其分级标准;然后应用偏序集评价模型得到Hasse图,并通过图展现的层集信息判别采空区塌陷危险程度;最后应用该模型对大宝山矿11个采空区的塌陷程度进行判别,评价结果准确合理。研究结果表明:该模型避免了以往研究中的赋权争议问题,克服了样本量不足致使模型无法应用的问题,而且能够应用更多的赋权方法识别排序的稳定程度,体现出样本间的分层信息。

关 键 词:偏序集  采空区塌陷  危险性评价  Hasse图  预测

Study on risk assessment of goaf collapse based on partial order set
HUANG Liang1,WANG Huimin1,' target="_blank" rel="external">2,YUE Lizhu3,JIN Shan1. Study on risk assessment of goaf collapse based on partial order set[J]. Journal of Safety Science and Technology, 2019, 15(4): 134-140. DOI: 10.11731/j.issn.1673-193x.2019.04.021
Authors:HUANG Liang1,WANG Huimin1,' target="  _blank"   rel="  external"  >2,YUE Lizhu3,JIN Shan1
Affiliation:(1.Mining Institute, Liaoning Technology University, Fuxin Liaoning 123000, China;2. School of Resources & Civil Engineering, Northeastern University, Shenyang Liaoning 110819, China;3.Public Administration and Law of Liaoning Technical University School, Fuxin Institute for Transformation and Innovation Development, Fuxin Liaoning 123000, China)
Abstract:Aiming at the problem of weighting disputes in the risk assessment method of goaf collapse, a partial order set evaluation model was proposed based on partial order set theory. The evaluation index was clarified and the grading criteria was determined. The Hasse diagram was obtained by using the partial order set evaluation model, and the risk of goaf collapse was distinguished by the layer set information presented by the Hasse diagram. The model is applied to distinguish the collapse degree of 11 goafs in Dabaoshan mine, and the evaluation results are accurate and reasonable. The results show that the model avoids the problem of weight disputes in previous studies, overcomes the problem that the model is not applicable due to the insufficient sample size, and can apply more weighting methods to identify the stability of the ranking, reflecting the differences between samples.
Keywords:partial order set   goaf collapse   risk assessment   hasse diagram   prediction
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