Deep learning-based prediction of effluent quality of a constructed wetland-Reference-Cited by-同舟云学术

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Deep learning-based prediction of effluent quality of a constructed wetland

Published:2023-01 Issue: Volume:13 Page:100207
ISSN:2666-4984
Container-title:Environmental Science and Ecotechnology
language:en
Short-container-title:Environmental Science and Ecotechnology

Author:

Yang Bowen,Xiao Zijie^ORCID,Meng Qingjie,Yuan Yuan,Wang Wenqian,Wang Haoyu,Wang Yongmei,Feng Xiaochi^ORCID

Funder

State Key Laboratory of Urban Water Resource and Environment

Basic and Applied Basic Research Foundation of Guangdong Province

National Natural Science Foundation of China

Guangdong Provincial Natural Science Foundation

Science, Technology and Innovation Commission of Shenzhen Municipality

Harbin Institute of Technology

Publisher

Elsevier BV

Subject

Environmental Science (miscellaneous),Ecology,Environmental Engineering

Reference35 articles.

1. Decomposition of pollutants from domestic sewage with the combination systems of hydrolytic acidification coupling with constructed wetland microbial fuel cell;Han;J. Clean. Prod.,2021

2. Multiphasic assessment of effects of design configuration on nutrient removal in storing multiple-pond constructed wetlands;Li;Bioresour. Technol.,2019

3. Site-specific carbon footprints of Scandinavian wastewater treatment plants, using the life cycle assessment approach;Delre;J. Clean. Prod.,2019

4. Analysis of the β-cyclodextrin enhancing bio-denitrification from the perspective of substrate metabolism, electron transfer, and iron acquisition;Shi;Chem. Eng. J.,2022

5. Removal of nutrients in saline wastewater using constructed wetlands: plant species, influent loads and salinity levels as influencing factors;Liang;Chemosphere,2017

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1. Pollution loads in the middle-lower Yangtze river by coupling water quality models with machine learning;Water Research;2024-10

2. Ecological threshold effect mediates the long-term synergistic management of mega-city runoff nutrients in large-scale hybrid constructed wetlands;Chemical Engineering Journal;2024-09

3. Optimization of a Novel Engineered Ecosystem Integrating Carbon, Nitrogen, Phosphorus, and Sulfur Biotransformation for Saline Wastewater Treatment Using an Interpretable Machine Learning Approach;Environmental Science & Technology;2024-07-10

4. Intelligent dosing of sodium hypochlorite in municipal wastewater treatment plants: Experimental and modeling studies;Journal of Water Process Engineering;2024-07

5. Water quality prediction based on sparse dataset using enhanced machine learning;Environmental Science and Ecotechnology;2024-07

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