郑州大学学报（工学版）2025，Vol.46Issue(3)：59-66,8.DOI:10.13705/j.issn.1671-6833.2024.06.014
基于BWO和WOA的VMD-LSTM短期风速预测
VMD-LSTM Short-term Wind Speed Prediction Model Based on BWO and WOA
摘要
Abstract
In view of the power fluctuation and randomness existing in the operation of wind turbine networks,to improve the accuracy of wind speed prediction and the stability of wind turbine operation,in this study a VMD-LSTM short-term wind speed prediction model was proposed based on the beluga whale optimization and the whale optimization algorithm.Firstly,the Beluga optimization algorithm was used to optimize the number of modes and penalty factors in VMD to obtain the reorganized subsequence.For parameters such as the number of hidden layer nodes,the maximum number of training generations,and the initial learning rate in LSTM,the whale optimization algorithm was used to determine these parameters.Finally,the monomer transplantation ability of LSTM was uti-lized to predict the data.The results indicated that the VMD-LSTM prediction model based on BWO and WOA pro-posed in this study achieved RMSE,MAE,and MAPE values of 0.223 4,0.172 7,and 0.083 7,respectively,on the test set,all of which were lower than those of other comparative models.This validated the effectiveness of the proposed model in short-term wind speed prediction.关键词
白鲸优化算法/鲸鱼优化算法/变分模态分解/LSTM/风速预测Key words
beluga whale optimization/whale optimization algorithm/variational mode decomposition/LSTM/wind speed prediction分类
计算机与自动化引用本文复制引用
贾世会,刘立夫,迟晓妮,李高西..基于BWO和WOA的VMD-LSTM短期风速预测[J].郑州大学学报（工学版）,2025,46(3):59-66,8.基金项目
国家自然科学基金资助项目(12361064) （12361064）
冶金工业过程系统科学湖北省重点实验室开放基金(z202301) （z202301）
