Probabilistic Prediction of Mine Dynamic Disaster Risk Based on Multiple Factor Pattern Recognition

Tianwei Lan; Chaojun Fan; Sheng Li; Hongwei Zhang; Andrian Sergaevich Batugin

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Probabilistic Prediction of Mine Dynamic Disaster Risk Based on Multiple Factor Pattern Recognition

机译：基于多因素模式识别的矿山动态灾害风险概率预测

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Rock burst and coal and gas outburst are the most serious dynamic disasters in coal mine and are affected by many factors, such as mining engineering environment. In order to accurately predict the risk area of mine dynamic disasters, a series of impact factors and events are classified, and the spatial data of these factors are managed on the basis of identifying the internal relationship between the impact factors and the disasters. A multifactor pattern recognition model is established by artificial intelligence. The risk probability prediction criteria of mine dynamic disasters and the risk probability values of each unit in the prediction area are determined by using the method of neural network and fuzzy mathematics. The dangerous area, threat area, and safety area of mine dynamic disasters are divided to evaluate the dangerous degree. The corresponding control measures for different dangerous areas are also put forward. Application of the prediction method of mine dynamic disaster factors based on pattern recognition, to improve the implementation of mine dynamic disaster prediction and controlling measures, guarantees the safe production of the coal mine.

机译：岩爆和煤与瓦斯突出是煤矿中最严重的动态灾害，受采矿工程环境等诸多因素的影响。为了准确预测矿山动态灾害的风险区域，对一系列影响因素和事件进行了分类，并在识别影响因素与灾害之间的内部关系的基础上，对这些因素的空间数据进行管理。通过人工智能建立了多因素模式识别模型。利用神经网络和模糊数学的方法，确定了矿山动态灾害的风险概率预测标准和预测区域内各单位的风险概率值。划分矿山动态灾害的危险区域，威胁区域和安全区域，以评估危险程度。并针对不同危险区域提出了相应的控制措施。基于模式识别的矿山动态灾害因素预测方法的应用，提高了矿山动态灾害预测控制措施的实施，保证了煤矿的安全生产。

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《Advances in civil engineering》 |2018年第2期|共页
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Tianwei Lan; Chaojun Fan; Sheng Li; Hongwei Zhang; Andrian Sergaevich Batugin;
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Probabilistic Prediction of Mine Dynamic Disaster Risk Based on Multiple Factor Pattern Recognition

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