现代信息科技2026，Vol.10Issue(8)：144-147,152,5.DOI:10.19850/j.cnki.2096-4706.2026.08.026
基于ARIMA-LSTM的地下水位预测模型
Groundwater Level Prediction Model Based on ARIMA-LSTM
摘要
Abstract
In order to address the problem of simultaneously considering linear and nonlinear characteristics in groundwater level prediction,a combined forecasting model based on the Autoregressive Integrated Moving Average Model and the Long Short-Term Memory Network(ARIMA-LSTM)is proposed.Firstly,the model employs the ARIMA model to handle the linear trends in the sequence.Then,it leverages the LSTM model's strong nonlinear fitting capability to correct the prediction errors(residuals)of the ARIMA model.Finally,by integrating the outputs of these two parts,more comprehensive and accurate groundwater level predictions are achieved.Experimental results show that the MAE,MSE,and RMSE of the groundwater level prediction model based on ARIMA-LSTM are 0.011 m,0.000 3 m,and 0.017 m,respectively,which are significantly lower than those of the single ARIMA and LSTM models.The smaller error of the ARIMA-LSTM model provides a reliable basis for the scientific evaluation and rational utilization of groundwater resources.关键词
地下水位/预测模型/时间序列/ARIMA/LSTMKey words
groundwater level/prediction model/time series/ARIMA/LSTM分类
信息技术与安全科学引用本文复制引用
张静..基于ARIMA-LSTM的地下水位预测模型[J].现代信息科技,2026,10(8):144-147,152,5.基金项目
水利部重大科技项目(SKS-2022142) （SKS-2022142）
2025年度河南省高等学校重点科研项目指导性计划(25B510010) （25B510010）
水利部黄河下游河道与河口治理重点实验室开放课题基金项目(2025007) （2025007）
