Modeling of Textile Dye Removal from Wastewater Using Innovative Oxidation Technologies (Fe(II)/Chlorine and H2O2/Periodate Processes): Artificial Neural Network-Particle Swarm Optimization Hybrid Model

被引：0

作者：

Fetimi, Abdelhalim ^{[1
]}

Merouani, Slimane ^{[2
]}

Khan, Mohd Shahnawaz ^{[3
]}

Asghar, Muhammad Nadeem ^{[4
]}

Yadav, Krishna Kumar ^{[5
]}

Jeon, Byong-Hun ^{[6
]}

Hamachi, Mourad ^{[1
]}

Kebiche-Senhadji, Ounissa ^{[1
]}

Benguerba, Yacine ^{[7
]}

机构：

[1] Univ Bejaia, Fac Technol, Lab Procedes Membranaires & Tech Separat & Recupe, Bejaia 06000, Algeria

[2] Univ Constantine 3 Salah Boubnider, Fac Proc Engn, Dept Chem Engn, Lab Environm Proc Engn, Constantine 25000, Algeria

[3] King Saud Univ, Dept Biochem, Coll Sci, Riyadh 11451, Saudi Arabia

[4] Univ Quebec Trois Rivieres, Dept Med Biol, Trois Rivieres, PQ G9A 5H7, Canada

[5] Madhyanchal Profess Univ, Fac Sci & Technol, Bhopal 462044, India

[6] Hanyang Univ, Dept Earth Resources & Environm Engn, Seoul 04763, South Korea

[7] Univ Ferhat ABBAS Setif 1, Fac Technol, Dept Proc Engn, Setif 19000, Algeria

来源：

ACS OMEGA | 2022年 / 7卷 / 16期

关键词：

POLYMER INCLUSION MEMBRANE; SUPPORTED LIQUID-MEMBRANE; PHOTOACTIVATED PERIODATE; AQUEOUS-SOLUTIONS; DEGRADATION; PREDICTION; TRANSPORT; CHROMIUM(VI); PERFORMANCE; ALGORITHM;

D O I：

10.1021/acsomega.2c0007413818

中图分类号：

O6 [化学];

学科分类号：

0703 ;

摘要：

An efficient optimization technique based on a metaheuristic and an artificial neural network (ANN) algorithm has been devised. Particle swarm optimization (PSO) and ANN were used to estimate the removal of two textile dyes from wastewater (reactive green 12, RG12, and toluidine blue, TB) using two unique oxidation processes: Fe(II)/chlorine and H2O2/periodate. A previous study has revealed that operating conditions substantially influence removal efficiency. Data points were gathered for the experimental studies that developed our ANN-PSO model. The PSO was used to determine the optimum ANN parameter values. Based on the two processes tested (Fe(II)/chlorine and H2O2/periodate), the proposed hybrid model (ANN-PSO) has been demonstrated to be the most successful in terms of establishing the optimal ANN parameters and brilliantly forecasting data for RG12 and TP elimination yield with the coefficient of determination (R2) topped 0.99 for three distinct ratio data sets.

引用

页码：13818 / 13825

页数：8

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