基于模糊神经网络的瓦斯安全状况预测模型  

Prediction model of gas safety status base on fuzzy nervous network

作　　者：魏永强[1] 甄选[1] 魏利娜[2] 王铭[1] 竹巍[1] 程彬彬[1] 

机构地区：[1]中国矿业大学(北京)资源与安全工程学院,北京100083 [2]河南师范大学化学与环境科学学院,河南新乡453007

出　　处：《煤炭工程》2010年第9期79-81,共3页Coal Engineering

摘　　要：从影响煤矿瓦斯安全因素的非线性特征出发,将模糊系统和人工神经网络有机结合,建立基于模糊神经网络的瓦斯安全状况预测模型。文章分析了模糊神经网络的结构、模糊神经元及其学习算法,介绍了煤矿瓦斯安全决策的模糊神经网络设计,依据实验分析,最终证明:该预测模型精确度很高,可以为瓦斯安全管理提供理论指导和辅助决策依据。From the nonlinear features affected to the mine gas safety factors,the fuzzy system and the artificial nervous network was organically combined to establish a prediction model of the gas safety status base on the fuzzy nervous network.The paper analyzed the structure of the fuzzy nervous network,the fuzzy nervous elements and the algorithm learning and introduced the design of the fuzzy nervous network for the mine gas safety decisions.According to the experiment analysis,the conclusion showed that the accuracy of the prediction model could be very high and could provide the theoretical guidance and support decision basis for the mine gas safety management.

关 键 词：瓦斯安全 模糊神经网络 神经元 

分 类 号：TD712.5[矿业工程—矿井通风与安全]