计算机与数字工程2026，Vol.54Issue(3)：630-633,657,5.DOI:10.3969/j.issn.1672-9722.2026.03.008
基于IWOA-LSTM的水利设施裂缝数据预测
Prediction of Fracture Data of Water Conservancy Facilities Based on IWOA-LSTM
摘要
Abstract
The crack width of water conservancy facilities has a great impact on the safe operation of water conservancy facili-ties,so it is necessary to predict the crack data.In this paper,a combined network model(IWOA-LSTM for short)based on im-proved whale optimization algorithm(IWOA)and long short term memory network(LSTM)is designed,which solves the influence of artificial setting super parameters on the prediction accuracy when the ordinary LSTM network predicts the fracture data of water conservancy facilities.Based on the existing whale optimization algorithm,the model adopts piecewise linear chaotic map to initial-ize the population,and introduces a nonlinear convergence factor to accelerate the population convergence.Combined with the crack data of No.4 headrace tunnel of a hydropower station,IWOA-LSTM model is used for prediction.The prediction results are compared with those of ARIMA model and single LSTM model.The results show that the R value of IWOA-LSTM model is in-creased by 10.95%and 4.69%respectively,indicating that the model has higher prediction accuracy.关键词
水利设施/时间序列预测/改进鲸鱼优化算法/长短期记忆网络Key words
water conservancy facilities/time series prediction/improved whale optimization algorithm/long short term memory network分类
信息技术与安全科学引用本文复制引用
袁自祥,杨涛,皮明..基于IWOA-LSTM的水利设施裂缝数据预测[J].计算机与数字工程,2026,54(3):630-633,657,5.基金项目
国家重点研发项目(编号:2019YFB1310504)资助. （编号:2019YFB1310504）
