基于瓦斯涌出的回采工作面参数识别BP神经网络模型

Identification BP nerve network model base on parameters of gas emission coal mining face

在分析回采工作面瓦斯涌出规律的基础上 ,运用BP人工神经网络模型 ,在给定工作面风量条件下 ,进行高瓦斯矿井回采工作面参数识别。合理地选择了采煤方法、循环作业方式、工作面推速度、工作面日产量等。模型精度很高 。

Base on the analysis of gas emission law in the coal mining faces, BP artificial nerve network model can identify the parameter of the coal mining face in high gassy mine with rated conditions of ventilation in the coal mining face. The model can rationally select a coal mining method, circulated operation method, face advancing rate, coal production per day per face and others. The model has a high accuracy and a certain practical value.