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Multi-step reservoir inflow prediction using a rolling window strategy and decomposed LSTM

Wandee Thaisiam Pongbavorn Rattanapant Pawit Kraisornnukhor Papis Wongchaisuwat

水科学与水工程2026，Vol.19Issue(1)：11-22,12.

水科学与水工程2026，Vol.19Issue(1)：11-22,12.DOI:10.1016/j.wse.2025.11.001

Multi-step reservoir inflow prediction using a rolling window strategy and decomposed LSTM

Wandee Thaisiam ¹Pongbavorn Rattanapant ¹Pawit Kraisornnukhor ²Papis Wongchaisuwat²

作者信息

1. Department of Water Resources Engineering,Kasetsart University,Bangkok 10900,Thailand
2. Department of Industrial Engineering,Kasetsart University,Bangkok 10900,Thailand
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摘要

关键词

Reservoir inflow forecasting/Deep learning/Long short-term memory network/Rolling window/Decomposition

Key words

Reservoir inflow forecasting/Deep learning/Long short-term memory network/Rolling window/Decomposition

引用本文复制引用

Wandee Thaisiam,Pongbavorn Rattanapant,Pawit Kraisornnukhor,Papis Wongchaisuwat..Multi-step reservoir inflow prediction using a rolling window strategy and decomposed LSTM[J].水科学与水工程,2026,19(1):11-22,12.

基金项目

This work was supported by the Faculty of Engineering,Kasetsart University,Bangkok,Thailand(Grant No.66/06/WE/M.Eng). （Grant No.66/06/WE/M.Eng）

水科学与水工程

ISSN：1674-2370

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