| 岩爆分级预测的粗糙集-多维正态云模型 |
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| 引用本文： | 刘冉,叶义成,张光权,姚囝,陈虎,王其虎.岩爆分级预测的粗糙集-多维正态云模型[J].金属矿山,2019,48(3):48-55. |
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| 作者姓名： | 刘冉 叶义成 张光权 姚囝 陈虎 王其虎 |
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| 作者单位： | 武汉科技大学资源与环境工程学院,湖北武汉,430081;武汉科技大学资源与环境工程学院,湖北武汉430081;湖北省工业安全工程技术研究中心,湖北武汉430081 |
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| 基金项目： | * 国家自然科学基金项目（编号：51574183），湖北省2017年安全生产专项(编号：2017HBAQZX)。 |
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| 摘 要： | 准确有效的岩爆分级预测对避免或减少岩爆灾害具有重要意义。选取围岩最大切向应力σθ、岩石单轴抗压强度σc、岩石单轴抗拉强度σt和岩石弹性变形能指数Wet作为岩爆评价指标，将多维正态云模型作为岩爆等级的预测方法，利用粗糙集确定评价指标权重，以国内外15组岩爆实例作为模型构建样本，建立了粗糙集-多维正态云岩爆分级预测模型。首先采用模糊集聚类后再通过粗糙集逐级筛选评价指标的方法确定评价指标权重，根据多维正态正向云发生器计算得到评价指标的确定度；然后利用评价指标权重和评价指标确定度计算评价样本的综合确定度，根据最大隶属度原则，判定评价样本的岩爆等级。采用鑫华矿业矿岩样本对粗糙集-多维正态云岩爆分级预测模型进行了有效性验证，计算结果与工程实际相吻合，表明该模型具有较好的实用性。
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| 关 键 词： | 岩爆 分级预测 粗糙集 多维正态云 综合确定度 |
Grading Prediction Model of Rockburst Based on Rough Set-Multidimensional Normal Cloud |
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| Liu Ran,Ye Yicheng,Zhang Guangquan,Yao Nan,Chen Hu,Wang Qihu.Grading Prediction Model of Rockburst Based on Rough Set-Multidimensional Normal Cloud[J].Metal Mine,2019,48(3):48-55. |
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| Authors: | Liu Ran Ye Yicheng Zhang Guangquan Yao Nan Chen Hu Wang Qihu |
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| Affiliation: | 1. School of Resource and Environmental Engineering，Wuhan University of Science and Technology，Wuhan 430081，China；2. Industrial Safety Engineering Technology Research Center of Hubei Province，Wuhan 430081，China |
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| Abstract: | Accurate and effective grading prediction of rockburst is of great significance to reduce rockburst disasters.Maximum tangential stress of surrounding rock σθ，uniaxial compressive strength of rock σc，uniaxial tensile strength of rock σt and elastic deformation energy index of rock Wet are selected as the evaluation indexes of rockburst.Multidimensional normal cloud model is used as the prediction method of rockburst grade.Rough set is used to determine the weight of evaluation indexes.15 sets of rockburst examples at home and abroad are used as model construction samples，and the grading prediction model of rockburst based on rough set-multidimensional normal cloud is established.Firstly，fuzzy clustering analysis is carried on the evaluation samples，the evaluation indexes are filtered through the rough set，and the weight of evaluation indexes is determined.The determination degree of evaluation indexes is calculated according to the multidimensional normal forward cloud generator.Then，the comprehensive determination degree of evaluation samples is calculated by using the weight of evaluation indexes and the determination degree of evaluation indexes.According to the principle of maximum membership degree，the rockburst grade of evaluation samples is determined.The rockburst samples of Xinhua Mining Company are used to validate the grading prediction model of rockburst based on rough set-multidimensional normal cloud.The calculated results are consistent with the actual situation，which further indicates that the grading prediction model of rockburst based on rough set-multidimensional normal cloud has great practicality. |
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| Keywords: | Rockburst Grading prediction Rough set Multidimensional normal cloud Comprehensive determination degree |
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