基于人工神经网络的矿井涌水量预测  

Forecasting the Water Yield of Coal Mine Based on the Artificial Neural Network

作　　者：赵向军[1] 李文平[1] 李龙海[1] 陈国锋[1] 

机构地区：[1]中国矿业大学,徐州221008

出　　处：《辽宁工程技术大学学报（自然科学版）》1998年第2期156-159,共4页Journal of Liaoning Technical University (Natural Science)

摘　　要：应用人工神经网络理论,提出了矿井涌水量预测的新方法,并将其与自回归时序模型进行了比较验证,结果表明,运用神经网络方法进行矿井涌水量预测,精度高,自适应性强,在数据不十分充足的情况下,效果尤其好于自回归模型。In this paper a new method has been advanced for forecasting the water yield of coal mining with application of the artificial neural network,and comparison is made with the result obtained from AR(P) model. The results show that the forecasting from this model is more consistent with the measured values when the quantity of data is not sufficient,its result is particularly better than that of AR(P) model.

关 键 词：人工神经网络 时间序列 矿井通水量 涌水量预测 

分 类 号：TD742.1[矿业工程—矿井通风与安全]