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基于神经网络的掘进面瓦斯爆炸危险源安全评价

Safety assessment of gas explosion hazard in heading face based on BP neural network

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【作者】 田水承; 李华; 陈勇刚;

【Author】 TIAN Shui-cheng1, LI Hua1, CHEN Yong-gang2 (1.School of Energy, Xi′an University of Science and Technology, Xi′an 710054 , China;2.Civil Aviation Flight University of China, Guanghan 618307, China)

【机构】 西安科技大学; 中国民航飞行学院 能源学院西安710054; 能源学院西安710054; 四川广汉618307;

【摘要】 根据危险源理论和评价指标选择原则,建立了掘进面瓦斯爆炸评价指标体系。基于灰色聚类评价法、BP神经网络原理和掘进面瓦斯爆炸的特点,设计了BP神经网络掘进面瓦斯爆炸危险源安全评价过程图。最后应用BP神经网络安全评价方法对具体的掘进面进行了安全评价,得出了安全评价等级。神经网络安全评价方法,能够实现动态、静态的安全评价,对提高安全评价技术水平具有现实的意义。

【Abstract】 According to hazard theory and principle of selecting assessment index, the paper constructs assessment index system of gas explosion in heading face. Based on the method of gray clustering, principle of BP neural network and characteristics of gas explosion in heading face, safety assessment procedural diagram of BP neural network on gas explosion hazard in heading face is designed. At the same time, gas explosion hazard of concrete heading face based on safety assessment method of BP neural network is assessed and grades of comprehensive safety assessment are achieved. The statistic and dynamic safety assessment can be realized by using safety assessment method of BP neural network. It is helpful to improve the level of safety management and technology of safety assessment.

【关键词】 神经网络; 安全评价; 瓦斯爆炸; 危险源;
【Key words】 neural network; safety assessment; gas explosion; hazard;
【基金】 陕西自然科学基金(2001C38);省教委专项基金(JK214);中国博士后科学基金(2003034462)
  • 【文献出处】 煤田地质与勘探 ,Coal Geology & Exploration , 编辑部邮箱 ,2005年03期
  • 【分类号】TD712.7
  • 【被引频次】48
  • 【下载频次】540
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