基于神经网络的矿井瓦斯涌出量预测系统及应用  

Neural Network-based Mine Gas Emission Predicting System and Its Application

作　　者：马俊枫[1] 史长胜[2] 

机构地区：[1]蚌埠坦克学院军事仿真室,安徽蚌埠233050 [2]淮南职业技术学院通风及安全工程系,安徽淮南232001

出　　处：《中国煤层气》2007年第1期30-33,共4页China Coalbed Methane

摘　　要：正确预测瓦斯涌出量,对于指导矿井设计和煤矿安全生产有重要的现实意义。为解决现有的矿井瓦斯涌出量预测方法不能实现自动化处理等问题,本文开发了基于神经网络的矿井瓦斯涌出量预测系统GGP,并介绍了该系统在实际工程上的应用情况。Accurate prediction of gas emission is of great practical significance in guiding mine design and ensuring work safety in coal mines. In order to solve the problem that automatic settlement can＇ t be realized with existing predicting methods for mine gas emission, the authors have developed the Neural Network-based GGP Mine Gas Emission Predicting System and introduced the application of the system in practical engineering.

关 键 词：神经网络 瓦斯预测 GGP预测系统 工程应用 

分 类 号：TD712.5[矿业工程—矿井通风与安全]