Techno-economical optimization of Reactive Blue 19 removal by combined electrocoagulation/coagulation process through MOPSO using RSM and ANFIS models.
In this research, Response Surface Methodology (RSM) and Adaptive Neuro Fuzzy Inference System (ANFIS) models were applied for optimization of Reactive Blue 19 removal using combined electrocoagulation/coagulation process through Multi-Objective Particle Swarm Optimization (MOPSO). By applying RSM,...
| Publicado en: | Journal of Environmental Management Vol. 128; pp. 798 - 807 |
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| Autores principales: | , , |
| Formato: | Artículo |
| Publicado: |
Academic Press Inc.
Oct2013
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| Materias: | |
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=90067516&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 90067516 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 03014797 EMJ jtl: Journal of Environmental Management issn: 03014797 maglogo: N pubinfo: dt: Oct2013 vid: 128 pid: 735 pub: Academic Press Inc. artinfo: ui: 90067516 10.1016/j.jenvman.2013.06.029 ppf: 798 ppct: 9 formats: tig: atl: Techno-economical optimization of Reactive Blue 19 removal by combined electrocoagulation/coagulation process through MOPSO using RSM and ANFIS models. aug: au: Taheri, M. Alavi Moghaddam, M.R. Arami, M. affil: Civil and Environmental Engineering Department, Amirkabir University of Technology (AUT), Hafez Ave., Tehran 15875-4413, Iran Textile Engineering Department, Amirkabir University of Technology (AUT), Hafez Ave., Tehran 15875-4413, Iran su: Electrocoagulation (Chemistry) Response surfaces (Statistics) Operating costs Reaction time Hydrogen-ion concentration Particle swarm optimization Aluminum chloride Dyes & dyeing sug: subj: All other basic inorganic chemical manufacturing Other Basic Inorganic Chemical Manufacturing Chemical (except agricultural) and allied product merchant wholesalers Synthetic Dye and Pigment Manufacturing Electrocoagulation (Chemistry) Response surfaces (Statistics) Operating costs Reaction time Hydrogen-ion concentration Particle swarm optimization Aluminum chloride Dyes & dyeing keyword: Adaptive Neuro Fuzzy Inference System Chemical coagulation Electrocoagulation Multi-Objective Particle Swarm Optimization Reactive Blue 19 Response Surface Methodology Adaptive Neuro Fuzzy Inference System Chemical coagulation Electrocoagulation Multi-Objective Particle Swarm Optimization Reactive Blue 19 Response Surface Methodology ab: In this research, Response Surface Methodology (RSM) and Adaptive Neuro Fuzzy Inference System (ANFIS) models were applied for optimization of Reactive Blue 19 removal using combined electrocoagulation/coagulation process through Multi-Objective Particle Swarm Optimization (MOPSO). By applying RSM, the effects of five independent parameters including applied current, reaction time, initial dye concentration, initial pH and dosage of Poly Aluminum Chloride were studied. According to the RSM results, all the independent parameters are equally important in dye removal efficiency. In addition, ANFIS was applied for dye removal efficiency and operating costs modeling. High R values (≥85%) indicate that the predictions of RSM and ANFIS models are acceptable for both responses. ANFIS was also used in MOPSO for finding the best techno-economical Reactive Blue 19 elimination conditions according to RSM design. Through MOPSO and the selected ANFIS model, Minimum and maximum values of 58.27% and 99.67% dye removal efficiencies were obtained, respectively. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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