Literature DB >> 16806684

The use of artificial neural networks (ANN) for modeling of decolorization of textile dye solution containing C. I. Basic Yellow 28 by electrocoagulation process.

N Daneshvar1, A R Khataee, N Djafarzadeh.   

Abstract

In this paper, electrocoagulation has been used for removal of color from solution containing C. I. Basic Yellow 28. The effect of operational parameters such as current density, initial pH of the solution, time of electrolysis, initial dye concentration, distance between the electrodes, retention time and solution conductivity were studied in an attempt to reach higher removal efficiency. Our results showed that the increase of current density up to 80 Am(-2) enhanced the color removal efficiency, the electrolysis time was 7 min and the range of pH was determined 5-8. It was found that for achieving a high color removal percent, the conductivity of the solution and the initial concentration of dye should be 10 mS cm(-1) and 50 mg l(-1), respectively. An artificial neural networks (ANN) model was developed to predict the performance of decolorization efficiency by EC process based on experimental data obtained in a laboratory batch reactor. A comparison between the predicted results of the designed ANN model and experimental data was also conducted. The model can describe the color removal percent under different conditions.

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Year:  2006        PMID: 16806684     DOI: 10.1016/j.jhazmat.2006.05.042

Source DB:  PubMed          Journal:  J Hazard Mater        ISSN: 0304-3894            Impact factor:   10.588


  4 in total

1.  Modeling and optimization of reductive degradation of chloramphenicol in aqueous solution by zero-valent bimetallic nanoparticles.

Authors:  Kunwar P Singh; Arun K Singh; Shikha Gupta; Premanjali Rai
Journal:  Environ Sci Pollut Res Int       Date:  2012-01-08       Impact factor: 4.223

2.  Integral approach of sorption coupled with biodegradation for treatment of azo dye using Pseudomonas sp.: batch, toxicity, and artificial neural network.

Authors:  Uttariya Roy; Shubhalakshmi Sengupta; Papita Das; Avijit Bhowal; Siddhartha Datta
Journal:  3 Biotech       Date:  2018-03-20       Impact factor: 2.406

3.  Degradation and mineralization of phenol compounds with goethite catalyst and mineralization prediction using artificial intelligence.

Authors:  Farhana Tisa; Meysam Davoody; Abdul Aziz Abdul Raman; Wan Mohd Ashri Wan Daud
Journal:  PLoS One       Date:  2015-04-07       Impact factor: 3.240

4.  BP-ANN Model Coupled with Particle Swarm Optimization for the Efficient Prediction of 2-Chlorophenol Removal in an Electro-Oxidation System.

Authors:  Yu Mei; Jiaqian Yang; Yin Lu; Feilin Hao; Dongmei Xu; Hua Pan; Jiade Wang
Journal:  Int J Environ Res Public Health       Date:  2019-07-10       Impact factor: 3.390

  4 in total

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