论文部分内容阅读
综采工作面产量、工效的预测，与采高、煤层倾角、煤层硬度、顶板类型、瓦斯、设备等因素有关，是一个复杂的非线性系统问题因而，用传统数学方法预测综采面产量往往误差较大运用人工神经元网络方法建立了综采面产量、工效预测模型，并实现了设备选型通过实例分析与实际情况对比，证明本模型有较高的实用价值
The prediction of fully mechanized mining face production and work efficiency is related to the factors such as mining height, coal seam dip angle, coal seam hardness, roof type, gas and equipment and so on. It is a complex nonlinear system problem. Therefore, the output of fully mechanized mining face Often with large error Using artificial neural network method to establish the production and efficiency prediction model of fully mechanized coal mining face and realize the equipment selection By comparing the actual case analysis and examples to prove that the model has a high practical value