Water quality prediction based on multi-task learning

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Date

2022

Journal Title

Journal ISSN

Volume Title

Publisher

MDPI

Abstract

Water pollution seriously endangers people’s lives and restricts the sustainable development of the economy. Water quality prediction is essential for early warning and prevention of water pollution. However, the nonlinear characteristics of water quality data make it challenging to accurately predicted by traditional methods. Recently, the methods based on deep learning can better deal with nonlinear characteristics, which improves the prediction performance. Still, they rarely consider the relationship between multiple prediction indicators of water quality. The relationship between multiple indicators is crucial for the prediction because they can provide more associated auxiliary information.

Description

Keywords

Water quality, Water pollution, Neural networks, Humans, China

Citation

Wu, H. et al. (2022). Water quality prediction based on multi-task learning. International journal of environmental research and public health, 19(15), 9699. https://doi.org/10.3390/ijerph19159699