计算机应用与软件2026，Vol.43Issue(4)：183-190,8.DOI:10.3969/j.issn.1000-386x.2026.04.026
基于VMD-GWO-LSTM的电热水器热水用量预测
PREDICTION OF HOT WATER CONSUMPTION OF ELECTRIC WATER HEATER BASED ON VMD-GWO-LSTM
摘要
Abstract
A hot water consumption prediction model based on VMD-GWO-LSTM is proposed to solve the problem of poor stability and large error caused by traditional prediction methods that ignore the timing of water consumption for water storage electric water heaters.VMD decomposed the original time series data to obtain modal components,and GWO optimized the LSTM network parameters for each component to establish an LSTM prediction model.The predicted values of hot water consumption for a certain period in the future were obtained by superposing the results of each prediction component.The prediction results of three typical operating conditions show that the correlation coefficient(R)of the optimized VMD-GWO-LSTM prediction is stable at above 98.60%,and the RMSE decreases by at least 61.7%compared with the prediction of the unoptimized LSTM,and the MAE decreases by at least 51.4%.Compared with the prediction of BP,SVM,GWO-LSTM,and VMD-LSTM,the prediction error is smaller and the stability is better,and the energy loss caused by the deviation in the supply of hot water due to the prediction error is reduced.关键词
LSTM/VMD/GWO/热水用量/电热水器Key words
LSTM/VMD/GWO/Hot water consumption/Electric water heater分类
信息技术与安全科学引用本文复制引用
陈庆明,孙颖楷,廖鸿飞..基于VMD-GWO-LSTM的电热水器热水用量预测[J].计算机应用与软件,2026,43(4):183-190,8.基金项目
广东省普通高校青年创新人才类项目(2021KQNCX231) （2021KQNCX231）
广东省高职院校产教融合创新平台项目(2020CJPT016). （2020CJPT016）
