基于模糊神经网络的瓦斯爆炸危险性评价模型  

Risk assessment model of gas explosion based on fuzzy neural network

作　　者：张爱然[1] 罗新荣[1] 杨飞[1] 康与涛[1] 

机构地区：[1]中国矿业大学安全工程学院,江苏徐州221008

出　　处：《黑龙江科技学院学报》2008年第1期54-57,共4页Journal of Heilongjiang Institute of Science and Technology

基　　金：国家自然科学基金重点项目(50534050);教育部科学技术研究重点项目(105025)

摘　　要：煤矿瓦斯爆炸事故的复杂性和随机性决定了煤矿瓦斯爆炸重大危险源的变化不会按照某一特定的规律或函数变化。模糊神经网络具有较强的非线性函数逼近能力和较强的自学习、自适应和联想能力。通过简化易燃、易爆、有毒重大危险源评价模型,确定了网络的输入参数,应用模糊神经网络对各参数之间的关系进行计算,验算结果表明:该网络模型在评价煤矿瓦斯爆炸危险性方面效果良好。Given conventional methods which fail to tackle the change of the major hazard of gas explosion arising out of the complexity and randomicity of the gas explosion accidents in coal mines, the paper features a solution based on the fuzzy neural network which combines the strongpoint of neural network and fuzzy theory. The paper introduces a new model based on the assessment model of combustible, explosive and poisonous major hazards, and offers the input parameters. The results indicated that the fuzzy neural network model allows a feasible assessment of the dangers of gas explosion.

关 键 词：模糊神经网络 瓦斯爆炸危险性 安全评价模型 

分 类 号：TD712[矿业工程—矿井通风与安全] TP183[自动化与计算机技术—控制理论与控制工程]