兖州矿区立井井筒非采动破裂的非线性预测与判别方法

THE NONLINEAR METHODS OF FORECAST AND JUDGMENT FOR SHAFT-LINING NON-MINING FRACTURE OF YANZHOU MINE

摘要: 厚冲积层立井井筒非采动破裂工程地质灾害是人类工程与自然环境相互作用的结果,该灾害的发生给煤矿造成巨大的经济损失,本文采用神经网络及模糊神经网络的方法对立井井筒破裂进行了预测与判别,预测与判别的结果表明,采用神经网络与模糊神经网络方法能够很好适用于立井井筒破裂的预测与判别,准确性高,能够满足实际应用的需要。

Abstract: Shaft-lining non-mining fracture is a kind of engineering geological hazard, which results from interaction between human engineering and natural environment and could cause great economic losses. The neural network and the fuzzy neural network methods are used for forecasting and judgment of shaft-lining fractures. The results show that neural network and fuzzy neural network methods can accurately predict occurrences of fractures and meet the need of practical application.