Adaptive period decomposition network with muti-scale temporal variation learning for water level prediction

Adaptive period decomposition network with muti-scale temporal variation learning for water level prediction

Study region:: Hanjiang River Basin, China Study focus:: This study introduces DLGNet, an advanced water level prediction model that employs an adaptive multi-resolution decomposition to decouple multiple periodic components. The model incorporates a 2D overlap patch attention mechanism and separabl...

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Bibliographic Details
Main Authors: Hui Wang, LiPing Wang, QiCang Qiu, Yuyan Gao, WenJuan Li, QiuShun Wang
Format: Article
Language:English
Published: Elsevier 2025-02-01
Series:Journal of Hydrology: Regional Studies
Subjects:
Time series
Water level prediction
Deep learning
Pattern recognition
Online Access:http://www.sciencedirect.com/science/article/pii/S2214581824004695
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