eprintid: 17667
rev_number: 2
eprint_status: archive
userid: 1
dir: disk0/00/01/76/67
datestamp: 2023-12-19 03:24:00
lastmod: 2023-12-19 03:24:00
status_changed: 2023-12-19 03:08:27
type: article
metadata_visibility: show
creators_name: Alhothali, A.
creators_name: Khurshid, H.
creators_name: Mustafa, M.R.U.
creators_name: Moria, K.M.
creators_name: Rashid, U.
creators_name: Bamasag, O.O.
title: Evaluation of Contemporary Computational Techniques to Optimize Adsorption Process for Simultaneous Removal of COD and TOC in Wastewater
ispublished: pub
keywords: Adsorption; Fuzzy inference; Genetic algorithms; Mean square error; Organic carbon, Adaptive neuro-fuzzy; Adsorption process; Chemical-oxygen demands; Computational technique; Means square errors; Methodology approaches; Response-surface methodology; Simultaneous removal; Surface plots; Total Organic Carbon, Chemical oxygen demand
note: cited By 4
abstract: This study was aimed at evaluating the artificial neural network (ANN), genetic algorithm (GA), adaptive neurofuzzy interference (ANFIS), and the response surface methodology (RSM) approaches for modeling and optimizing the simultaneous adsorptive removal of chemical oxygen demand (COD) and total organic carbon (TOC) in produced water (PW) using tea waste biochar (TWBC). Comparative analysis of RSM, ANN, and ANFIS models showed mean square error (MSE) as 5.29809, 1.49937, and 0.24164 for adsorption of COD and MSE of 0.11726, 0.10241, and 0.08747 for prediction of TOC adsorption, respectively. The study showed that ANFIS outperformed the ANN and RSM in terms of fast convergence, minimum MSE, and sum of square error for prediction of adsorption data. The adsorption parameters were optimized using ANFIS-surface plots, ANN-GA hybrid, RSM-GA hybrid, and RSM optimization tool in design expert (DE) software. Maximum COD (88.9) and TOC (98.8) removal were predicted at pH of 7, a dosage of 300 mg/L, and contact time of 60 mins using ANFIS-surface plots. The optimization approaches showed the performance in the following order: ANFIS-surface plots>ANN-GA>RSM-GA>RSM. © 2022 Areej Alhothali et al.
date: 2022
publisher: Hindawi Limited
official_url: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85129963871&doi=10.1155%2f2022%2f7874826&partnerID=40&md5=5c6cd10cb90c144d2a5f8a9fe125bd52
id_number: 10.1155/2022/7874826
full_text_status: none
publication: Adsorption Science and Technology
volume: 2022
refereed: TRUE
issn: 02636174
citation:   Alhothali, A. and Khurshid, H. and Mustafa, M.R.U. and Moria, K.M. and Rashid, U. and Bamasag, O.O.  (2022) Evaluation of Contemporary Computational Techniques to Optimize Adsorption Process for Simultaneous Removal of COD and TOC in Wastewater.  Adsorption Science and Technology, 2022.   ISSN 02636174