Artificial neural network implementation for dissolved organic carbon quantification using fluorescence intensity as a predictor in wastewater treatment plants-Reference-Cited by-同舟云学术

Artificial neural network implementation for dissolved organic carbon quantification using fluorescence intensity as a predictor in wastewater treatment plants

Published:2023-09 Issue: Volume:335 Page:139032
ISSN:0045-6535
Container-title:Chemosphere
language:en
Short-container-title:Chemosphere

Author:

Nurhayati Mita^ORCID,You Youngmin,Park Jongkwan,Lee Byung Joon,Kang Ho Geun^ORCID,Lee Sungyun

Funder

Ministry of SMEs and Startups

National Research Foundation of Korea

Publisher

Elsevier BV

Subject

General Medicine,General Chemistry,Environmental Chemistry,Environmental Engineering,Pollution,Health, Toxicology and Mutagenesis,Public Health, Environmental and Occupational Health

Reference67 articles.

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3. Experimental Application of an Advanced Separation Process for NOM Removal from Surface Drinking Water Supply;Callegari,2017

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5. Role of non-fluorescent chromophores in inner filter effect correction and PARAFAC decomposition;Carstea;Spectrochim. Acta Mol. Biomol. Spectrosc.,2020

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