Identification of pollution source and prediction of water quality based on deep learning techniques-Reference-Cited by-同舟云学术

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Identification of pollution source and prediction of water quality based on deep learning techniques

Published:2024-02 Issue: Volume:261 Page:104287
ISSN:0169-7722
Container-title:Journal of Contaminant Hydrology
language:en
Short-container-title:Journal of Contaminant Hydrology

Author:

Wang Junping,Xue Baolin,Wang Yuntao,A Yinglan,Wang Guoqiang,Han Dongqing

Funder

National Key Research and Development Program of China

Publisher

Elsevier BV

Subject

Water Science and Technology,Environmental Chemistry

Reference35 articles.

1. Integrated use of satellite remote sensing, artificial neural networks, field spectroscopy, and GIS in estimating crucial soil parameters in terms of soil erosion;Alexakis;Remote Sens.,2019

2. Multivariate Time Series Forecasting with Lstm for Madrid, Spain Pollution;Alhirmizy,2019

3. Predicting river water quality index using data mining techniques;Babbar;Environ. Earth Sci.,2017

4. Determining quality of water in reservoir using machine learning;Chou;Ecol. Inform.,2018

5. Synthesizing water quality indicators from standardized geospatial information to remedy water security challenges: a review;de Paul Obade;Environ. Int.,2018

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4. Assessment of surface water quality in the Siversky Donets river within Kharkiv region in 2023;Man and Environment. Issues of Neoecology;2024-06-28

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