Issue |
E3S Web Conf.
Volume 580, 2024
2024 2nd International Conference on Clean Energy and Low Carbon Technologies (CELCT 2024)
|
|
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Article Number | 01007 | |
Number of page(s) | 6 | |
Section | Energy System Modeling and Ecological Resource Management | |
DOI | https://doi.org/10.1051/e3sconf/202458001007 | |
Published online | 23 October 2024 |
Research on Watershed Water Quality Classification Prediction Based on WOA-CNN-GRU Model
1 School of Information Technology, Mapua University, Manila 1002, Philippines
2 School of Information Engineering, Yulin University, Yulin 719000, Shaanxi, China
* Corresponding author: b EBBlancaflor@mapua.edu.ph;
a mwu@mymail.mapua.edu.ph
River water quality monitoring plays a crucial role in water environment protection and management. This paper aims to explore and innovatively propose an efficient and accurate water quality classification prediction model WOA-CNN-GRU composite model. By ingeniously integrating WOA, GRU, and CNN, this model conducts comprehensive predictive research on the complex and dynamic water quality environments of the Yellow River basins in China. Addressing limitations of traditional water quality prediction methods such as single-model approaches, inadequate data processing capabilities, and limited prediction accuracy, the WOA-CNN-GRU model constructed in this study integrates core technologies from different algorithms to achieve comprehensive analysis and efficient handling of water quality data.
© The Authors, published by EDP Sciences, 2024
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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