An improved graph neural network integrating indicator attention and spatio-temporal correlation for dissolved oxygen prediction

An improved graph neural network integrating indicator attention and spatio-temporal correlation for dissolved oxygen prediction

Accurately predicting dissolved oxygen (DO) is essential for water environment protection and management. The spatiotemporal dependencies of water quality and the interactions between indicators are neglected in existing prediction models. To improve the DO prediction accuracy, a graph neural networ...

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Bibliographic Details
Main Authors: Fei Ding, Shilong Hao, Mingcen Jiang, Hongfei Liu, Jingjie Wang, Bing Hao, Haobin Yuan, Hanjie Mao, Yang Hu, Wenpan Li, Xin Xie, Yong Zhang
Format: Article
Language:English
Published: Elsevier 2025-07-01
Series:Ecological Informatics
Subjects:
Graph neural networks
Indicator attention mechanism
Bayesian optimization
Dissolved oxygen prediction
Deep learning
Online Access:http://www.sciencedirect.com/science/article/pii/S1574954125001359
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