神经网络在判别煤矿突水水源中的应用  

Application of Neural Network in Discriminating Water Bursting Source of the Coal Mine

作　　者：魏永强[1] 梁化强[1] 任印国[1] 刘伟[1] 

机构地区：[1]中国矿业大学资源与地球科学学院,江苏徐州221008

出　　处：《江苏地质》2004年第1期36-38,共3页Jiangsu Geology

摘　　要：矿井突水水源的识别是矿井防治水工作的基础 ,快速准确地判别突水的来源对整个矿井的安全生产起着十分重要的作用。以峰峰矿区梧桐庄矿为例 ,应用神经网络的方法 ,对矿井突水水源进行了系统研究。结果表明 ,运用该方法取得了较好的效果 ,并可以用此模型来解决类似的评价和判别问题。The discrimination of the mine water-bursting source is deemed to be a basic knowledge for the water control in the mines. A speedy and precise discrimination is of key importance to the safe production of the whole mine. In the text, Fengfeng Mine is adopted as an example for the use of neural network method and for a systematic study of water bursting source of the mine. It is concluded that the result of neural network method is effective and can be used to solve the issues like the appraisal and distinguish of water bursting.

关 键 词：突水水源 神经网络 评价和判别 

分 类 号：TP183[自动化与计算机技术—控制理论与控制工程]