A method for predicting water quality of river basin based on OVMD-GAT-GRU-Reference-Cited by-同舟云学术

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A method for predicting water quality of river basin based on OVMD-GAT-GRU

Published:2023-10-12 Issue:1 Volume:38 Page:339-356
ISSN:1436-3240
Container-title:Stochastic Environmental Research and Risk Assessment
language:en
Short-container-title:Stoch Environ Res Risk Assess

Author:

Song Jinling^ORCID,Meng Haitao^ORCID,Kang Yan,Zhu Meining,Zhu Yijin,Zhang Jingwu

Funder

S&T Program of Hebei

2023 Scientific Research Project of Higher Education Institutions in Hebei Province

Publisher

Springer Science and Business Media LLC

Subject

General Environmental Science,Safety, Risk, Reliability and Quality,Water Science and Technology,Environmental Chemistry,Environmental Engineering

Link

https://link.springer.com/content/pdf/10.1007/s00477-023-02584-0.pdf

Reference41 articles.

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2. Bruna J, Zaremba W, Szlam A, LeCun Y (2013) Spectral networks and locally connected networks on graphs. https://doi.org/10.48550/arXiv.1312.6203

3. Cho K, Merrienboer BV, Gülçehre Ç, Bougares F, Schwenk H, Bengio Y (2014) Learning phrase representations using rnn encoder-decoder for statistical machine translation. https://doi.org/10.48550/arXiv.1406.1078

4. Dai G, Ma C, Xu X (2019) Short-term traffic flow prediction method for urban road sections based on space-time analysis and GRU. IEEE Access 7:143025–143035. https://doi.org/10.1109/ACCESS.2019.2941280

5. Diao Z, Wang X, Zhang D, Liu Y, Xie K, He S (2019) Dynamic spatial-temporal graph convolutional neural networks for traffic forecasting. Proc AAAI Conf Artif Intell 33:890–897. https://doi.org/10.1609/aaai.v33i01.3301890

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1. Total suspended particulates prediction method for intensive waterfowl farming;Proceedings of the 2023 3rd Guangdong-Hong Kong-Macao Greater Bay Area Artificial Intelligence and Big Data Forum;2023-09-22

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