›› 2017, Vol. 38 ›› Issue (S2): 257-265.doi: 10.16285/j.rsm.2017.S2.036

• 基础理论与实验研究 • 上一篇    下一篇

基于指标距离与不确定度量的岩爆云模型预测研究

张 彪,戴兴国   

  1. 中南大学 资源与安全工程学院,湖南 长沙 410083
  • 收稿日期:2017-05-14 出版日期:2017-11-23 发布日期:2018-06-05
  • 通讯作者: 戴兴国,男,1958年生,博士,博士后,博士生导师,主要从事采矿工艺、岩土力学方面的研究和教学工作。E-mail: xgdai@mail.csu.edu.cn E-mail: Kenway@csu.edu.cn
  • 作者简介:张彪,男,1992年生,硕士研究生,主要从事矿业系统工程、风险评估与管理等方面的研究。

A cloud model for predicting rockburst intensity grade based on index distance and uncertainty measure

ZHANG Biao, DAI Xing-guo   

  1. School of Resources and Safety Engineering, Central South University, Changsha, Hunan 410083, China
  • Received:2017-05-14 Online:2017-11-23 Published:2018-06-05

摘要: 岩爆灾害预测是一个需要迫切解决的世界性难题。针对其烈度等级预测过程中评价指标实测值的确定与不确定性、烈度分级的模糊性和随机性等特点,提出了一种基于指标距离与不确定度量的有限区间云模型岩爆烈度分级预测方法。在对岩爆发生机制进行系统性分析的基础上,建立了岩爆烈度分级预测的评价指标体系,并对各指标实测值赋予其相应的Mass函数,依据指标间距离与不确定性度量获取指标权值,对传统云模型加以修正,并计算出各判别因子隶属于各等级的云特征参数,生成相应的云滴图,实现了语意变量与指标值之间的不确定性和随机性映射。通过对各指标的确定度进行加权实现岩爆烈度的分级。与其他理论相对比分析结果表明,该模型一定程度上应用于岩爆烈度分级预测是行之有效的,具有较高的实用性和指导性,并为其他同类型问题提供了新思路。

关键词: 岩爆烈度预测, 指标距离, 不确定度量, 有限区间云模型

Abstract: Rockburst disaster prediction is still an unsolvable global problem in underground rock engineering construction at present; to predict the rockburst intensity grade, a prediction method of rockburst intensity classification of finite intervals cloud model based on index distance and uncertainty measure is proposed to overcome the measured index values of certainty and uncertainty, intensity classification are of fuzzy and random in predicting. The evaluation index system of rockburst intensity classification forecasting is first established based on a comprehensive analysis of the rockburst mechanism and the Mass function of each index is calculated by the ridge function, the weight coefficients are second obtained based on the index distances and uncertainty measure. Then the normal cloud theory is modified and used to calculate the cloud characteristics for each evaluation index in rockburst classification, which generates the cloud drops in finite intervals, combined the measured index values with the corresponding weights the comprehensive degrees of certainty are obtained; and the rockburst level is identified by the weighted average principle in the end; the uncertainty and randomness mapping between the semantic variable and the evaluation index value are realized. The actual cases are introduced to further explain the calculation flow of the prediction model; and comparing with other theory methods shows that the model proposed is effective for rockburst classification to a certain extent; and its accuracy is higher than the other methods, so as to provide a novel idea for similar engineering problems.

Key words: rockburst intensity prediction, distance of index, uncertainty measure, finite cloud model

中图分类号: 

  • TU457

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