基于贝叶斯网络的金属矿山冒顶片帮事故预测评价

来源期刊：有色金属2011年第2期

论文作者：李莹莹 叶义成 吕垒 黄军

文章页码：255 - 259

关键词：采矿工程； 冒顶片帮； 贝叶斯网络； 预测； 重要度

Key words：mining engineering； roof falling and rib spalling； Bayesian network； forecast； importance degree

摘    要：针对金属矿山中冒顶片帮事故受多种控制因素影响,具有随机不确定性、概率性的预测评价难点,利用贝叶斯网络推理方法,建立金属矿山冒顶片帮事故BN预测评价模型。应用研究证明,金属矿山冒顶片帮事故BN模型具有强大推理功能,适应对不确定的知识和信息作出推理和判断,能够有效地预测冒顶片帮事故发生的概率以及评价基本事件的重要程度,可为金属矿山冒顶片帮事故预防和安全管理提供科学的决策依据。

Abstract: The accidents by roof falling and rib spalling did a great deal of economic loss with some casualties,which make a strong impact on the normal production safety.These accidents are uncertainty and probabilities,which affected by a variety of control factors.Cope with this problem,a forecasting and evaluation model is used to forecast the accidents by roof falling and rib spalling is built based on the theory of Bayesian network in this paper.Applications in practical engineering have shown that this forecasting and evaluation model has a powerful inferring ability,and is appropriate to judge and reason the uncertainty of knowledge and information.This model can forecast the probability of accidents,and evaluate the importance of the basic events.It provides an scientific proof for prevention and safety management on the accidents by roof falling and rib spalling in metal mining.