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基于神经网络的自然发火危险性评价与预测
引用本文:桂祥友,郁钟铭,孟絮屹.基于神经网络的自然发火危险性评价与预测[J].采矿与安全工程学报,2008,25(4).
作者姓名:桂祥友  郁钟铭  孟絮屹
作者单位:1. 贵州大学矿业学院,贵州,贵阳,550003
2. 武汉理工大学管理学院,湖北,武汉,430070;贵州民族学院管理学院,贵州,贵阳,550025
基金项目:教育部春晖计划项目,贵州省国际合作项目,贵州大学引进人才项目,贵州省优秀青年人才项目
摘    要:对采空区煤炭自然发火进行了危险性评价,从自然发火条件入手,建立采空区自然发火事故模型,确定采空区发火现状危险等级为C级,较危险;利用采空区已有的自然发火预测指标建立BP神经网络的时间序列预测模型,对未来该采空区有无发火危险进行了预测,确定未来采空区发火可能性大小.结果表明:运用BP神经网络的时间序列预测模型对煤炭自然发火进行预测,采空区自然发火处于"有发火危险"程度,发火危险性较大,因此应做好采空区火灾预防工作.

关 键 词:矿业安全  自然发火  危险性评价  神经网络  预测

Evaluation and Prediction of Coal Spontaneous Combustion Hazards Risk Based on Neural Network
GUI Xiang-you,YU Zhong-ming,MENG Xu-yi.Evaluation and Prediction of Coal Spontaneous Combustion Hazards Risk Based on Neural Network[J].Journal of Mining and Safety Engineering,2008,25(4).
Authors:GUI Xiang-you  YU Zhong-ming  MENG Xu-yi
Affiliation:1.College of Mining;Guizhou University;Guiyang;Guizhou 550003;China;2.College of Management;Wuhan University of Technology;Wuhan;Hubei 430070;3.College of Management;Guizhou University of Nationalities;Guizhou 550025;China
Abstract:Risk of coal spontaneous combustion in goaf was evaluated and the incident model of spontaneous combustion established to determine the risk grade.The result shows that this risk grade is C,which means "quite dangerous".In addition,the time series prediction model based on BP neural network was also set up by using of forecasting indexes of goaf spontaneous ignition.By using this model,we forecast future risk of spontaneous combustion,showing that the goaf is in danger of spontaneous combustion.So preventio...
Keywords:mine safety  spontaneous ignition  slope hazards risk evaluation  neural network  forecast  
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