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https://doi.org/10.15255/KUI.2020.071

Ternary Multicomponent Adsorption Modelling Using ANN, LS-SVR, and SVR Approach – Case Study

Amina Yettou ; Laboratory of Biomaterials and Transport Phenomena (LBMPT), University of Médéa, Médéa, Alžir
Maamar Laidi orcid id orcid.org/0000-0002-8977-9895 ; Laboratory of Biomaterials and Transport Phenomena (LBMPT), University of Médéa, Médéa, Alžir
Abdelmadjid El Bey orcid id orcid.org/0000-0002-5525-074X ; Laboratory of Biomaterials and Transport Phenomena (LBMPT), University of Médéa, Médéa, Alžir
Salah Hanini ; Laboratory of Biomaterials and Transport Phenomena (LBMPT), University of Médéa, Médéa, Alžir
Mohamed Hentabli orcid id orcid.org/0000-0002-6693-0708 ; Laboratory Quality Control, Physico-Chemical Department, Antibiotical Saidal of Médéa, Alžir
Omar Khaldi ; Material and Environment Laboratory (LME), University Yahia Fares of Medea, Médéa, Alžir
Mihoub Abderrahim ; Laboratory of Biomaterials and Transport Phenomena (LBMPT), University of Médéa, Médéa, Alžir


Puni tekst: engleski pdf 1.056 Kb

str. 509-518

preuzimanja: 242

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Sažetak

The aim of this work was to develop three artificial intelligence-based methods to model the ternary adsorption of heavy metal ions {Pb2+, Hg2+, Cd2+, Cu2+, Zn2+, Ni2+, Cr4+} on different adsorbates {activated carbon, chitosan, Danish peat, Heilongjiang peat, carbon sunflower head, and carbon sunflower stem). Results show that support vector regression (SVR) performed slightly better, more accurate, stable, and more rapid than least-square support vector regression (LS-SVR) and artificial neural networks (ANN). The SVR model is highly recommended for estimating the ternary adsorption kinetics of a multicomponent system.




This work is licensed under a Creative Commons Attribution 4.0 International License.

Ključne riječi

multicomponent adsorption; heavy metals; artificial neural networks; support vector regression; least-square support vector regression

Hrčak ID:

261417

URI

https://hrcak.srce.hr/261417

Datum izdavanja:

23.8.2021.

Podaci na drugim jezicima: hrvatski

Posjeta: 782 *