南昌工程学院学报2024，Vol.43Issue(3)：8-12,5.
SARIMA-GRU组合模型的水位预测
Water level forecasting based on SARIMA-GRU combination model
摘要
Abstract
Compared with traditional single models,combination models have better predictive accuracy under certain condi-tions.To verify whether the combination model is conducive to improving the prediction accuracy of the model,the water lev-el data of Shigui Mountain hydropower station,a tributary of the Yangtze River in the middle reaches are used as the basis.SARIMA model and GRU neural network model are established.The two models are then combined using the inverse vari-ance weighted average method and the IOWA operator.Finally,the predictive accuracy difference between the single model and the combination model is compared with the water level dataset.The results show that appropriate combination methods are conducive to improving model predictive accuracy,and the combination model based on the IOWA operator has excellent predictive performance.关键词
SARIMA/GRU神经网络/水位预测/组合模型Key words
SARIMA/GRU neural network/water level forecasting/combination model分类
建筑与水利引用本文复制引用
曹寒问,陈九江,李小玲..SARIMA-GRU组合模型的水位预测[J].南昌工程学院学报,2024,43(3):8-12,5.基金项目
江西省高校人文社会科学研究项目(TJ23101) （TJ23101）
