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