Modeling of a full-scale sewage treatment plant to predict the nutrient removal efficiency using a long short-term memory (LSTM) neural network-Reference-Cited by-同舟云学术

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Modeling of a full-scale sewage treatment plant to predict the nutrient removal efficiency using a long short-term memory (LSTM) neural network

Published:2020-10 Issue: Volume:37 Page:101388
ISSN:2214-7144
Container-title:Journal of Water Process Engineering
language:en
Short-container-title:Journal of Water Process Engineering

Author:

Yaqub Muhammad,Asif Hasnain,Kim Seongboem,Lee Wontae

Funder

Korea Environment Corporation, Geum River Environmental Management Office

Okcheon-gun

National Information Society Agency

Publisher

Elsevier BV

Subject

Process Chemistry and Technology,Waste Management and Disposal,Safety, Risk, Reliability and Quality,Biotechnology

Reference50 articles.

1. Research progress on ecological models in the field of water eutrophication: citespace analysis based on data from the ISI web of science database;Hu;Ecol. Modell.,2019

2. Anthropogenic pollution of aquatic ecosystems: emerging problems with global implications;Häder;Sci. Total Environ.,2020

3. Water eutrophication assessment relied on various machine learning techniques: a case study in the Englishmen Lake (Northern Spain);Nieto;Ecol. Modell.,2019

4. A review of phosphorus removal technologies and their applicability to small-scale domestic wastewater treatment systems;Bunce;Front. Environ. Sci.,2018

5. Technologies to recover nutrients from waste streams: a critical review;Mehta;Crit. Rev. Environ. Sci. Technol.,2015

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