CAJ | 학술논문

分析了影响导水裂隙带高度的因素，并将其分为主要因素和次要因素，构建了导水裂隙带高度影响因素体系。采用BP神经网络模型，并选取煤层厚度、顶板岩性、煤层倾角、覆岩硬度、工作面斜长、推进速度、岩体碎胀性作为主要因素用于导水裂隙带高度的预测，为了简化预测模型，加快计算速度，在确定的采矿地质条件下可忽略次要因素。预测结果表明，简化的BP神经网络模型能够满足导水裂隙带高度预测的准确度需要，该预测方法可为水体下采煤提供一定的技术指导。
분석료영향도수렬극대고도적인소，병장기분위주요인소화차요인소，구건료도수렬극대고도영향인소체계。채용BP신경망락모형，병선취매층후도、정판암성、매층경각、복암경도、공작면사장、추진속도、암체쇄창성작위주요인소용우도수렬극대고도적예측，위료간화예측모형，가쾌계산속도，재학정적채광지질조건하가홀략차요인소。예측결과표명，간화적BP신경망락모형능구만족도수렬극대고도예측적준학도수요，해예측방법가위수체하채매제공일정적기술지도。
In this paper, analysis was made on the factors affecting the height of water flowing fractured zone, which were then divided into the primary and secondary factors, and a system of factors affecting the height of water flowing fractured zone was constructed. BP neural network model was adopted and the thickness of coal seam, the lithological properties of roof rock, the dip angle of coal seam, the hardness of overlying rock, the inclined length of the working face, the advance speed and the bulking deformation of rock mass were chosen as the primary factors for predicting the height of the water flowing fractured zone, Under the determined geological condition, the secondary factors can be ignored in order to simplify the prediction model and accelerate the calculation. The prediction results showed that the simplified BP neural netwook model could meet the prediction accuracy of the height of water flowing fractured zone and this prediction method could provide a certain technical guidance for coal mining under water-bodies.