Modelling coagulant dosage in drinking water treatment plant using advance machine learning model: Hybrid extreme learning machine optimized by Bat algorithm-Reference-Cited by-同舟云学术

Modelling coagulant dosage in drinking water treatment plant using advance machine learning model: Hybrid extreme learning machine optimized by Bat algorithm

Published:2023-05-12 Issue:28 Volume:30 Page:72463-72483
ISSN:1614-7499
Container-title:Environmental Science and Pollution Research
language:en
Short-container-title:Environ Sci Pollut Res

Author:

Boumezbeur Hemza,Laouacheria Fares^ORCID,Heddam Salim^ORCID,Djemili Lakhdar

Publisher

Springer Science and Business Media LLC

Subject

Health, Toxicology and Mutagenesis,Pollution,Environmental Chemistry,General Medicine

Link

https://link.springer.com/content/pdf/10.1007/s11356-023-27224-6.pdf

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2. Arab M, Akbarian H, Gheibi M, Akrami M, Fathollahi-Fard AM, Hajiaghaei-Keshteli M, Tian G (2022) A soft-sensor for sustainable operation of coagulation and flocculation units. Eng Applic Artif Intell 115:105315. https://doi.org/10.1016/j.engappai.2022.105315

3. Ahammed MM, Gadekar M (2021) Modeling undefined complexities of wastewater treatment processes with artificial neural network. In: Soft computing techniques in solid waste and wastewater management. Elsevier, pp 365–379. https://doi.org/10.1016/B978-0-12-824463-0.00006-9

4. Beluli VM (2020) Kinetics of oxidation of manganese by potassium permanganate and chloride in the Velekinca water treatment plant, Kosovo. J Water Land Dev https://doi.org/10.24425/jwld.2020.135029

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