小波神经网络模型在地下水预测中的应用

Application of wavelet neural network model in Liaoning Plain Groundwater Prediction

应用小波神经网络模型对辽中平原地区地下水进行预测,并结合区域内实测的地下水水位井观测数据,分析了小波神经网络模型在地下水预测的适用性。研究结果表明：小波神经网络模型在辽中平原地区地下水预测具有较好的预测精度,预测和实测地下水水位之间的相对误差均在15%以内,绝对误差在0.08~2.39mm之间。研究成果对于辽中地区地下水预测具有参考价值。

In this paper, wavelet neural network model Liao Plain groundwater forecast, combined with groundwater level observation wells in the region measured data, analyzes the wavelet neural network model to predict groundwater applicability. The results show that： wavelet neural network model to predict groundwater Liaoning plain area has better prediction accuracy, the relative error of the measured groundwater levels and groundwater levels measured between are less than 15% absolute error between mm. Research for prediction of groundwater in central Liaoning reference value.