基于人工神经网络技术的综放导水断裂带高度预计

在对综放开采条件下导水断裂带发育规律分析的基础上，将基于非线性理论的人工神经网络技术用于煤层覆岩破坏高度的预测，选取采高、基岩柱厚度、倾角、顶板单轴压强度、泥岩比例和覆岩结构6种因素作为导水断裂带预测模型的影响因子，建立导水断裂带高度预测模型，并在我国首个海域下综放工作面加以应用.

Height forecast of water conducted zone with top coal caving based on artificial neural network

Based on the analysis of the water contucted zones development rule  with fully mechanized top coal caving，forecased the height of seam overlying rock using  artificial neural network technology Six influence factors of water contucted zones height were selected，viz mining height，base rock thickness，obliquity，uniaxial compressing strength of roof，scale of mudstone in overlying rock，and structure of overlying rock The height forecast model of water contucted zones  was established based on artificial neural network，and which was applied in the first fully mechanized top coal caving face under sea in China.