【摘要】 综放工作面为复杂的非线性系统 ,其设备与放煤工艺参数的选择和技术经济指标的预测 ,是复杂的非线性问题 ,用传统的数学方法难于解决 .应用神经网络方法建立了综放工作面产量、工效及采出率的预测模型 ,并实现了采煤机、液压支架选型和放煤方式、放煤步距的优化 .实际应用结果表明 ,模型的可靠性及精度高 ,有较大的实用价值更多还原

【Abstract】 Fully mechanized sub level caving face is a complicated non linear system, and the selection of equipment and technological parameters for coal drawing and the forecast of technical economic indexes of the face are complicated non linear problems which are difficult to solve with traditional mathematical method. A neural network model is established to predict face production, efficiency and recovery rate, to select shearer and powered supports and to optimize coal drawing method and interval. The results of actual application indicate that the model is reliable and precise and has larger practical value.更多还原