• May 15, 2019 News!Vol.7, No.5- Vol.8, No.4 has been indexed by EI (Inspec).   [Click]
  • Aug 01, 2018 News! [CFP] 2020 the annual meeting of IJMO Editorial Board, ECDMO 2020, will be held in Athens, Greece, February 15-17, 2020.   [Click]
  • Sep 30, 2019 News!Vol 9, No 6 has been published with online version. 12 original aritcles from 6 countries are published in this issue.    [Click]
General Information
    • ISSN: 2010-3697  (Online)
    • Abbreviated Title: Int. J. Model. Optim.
    • Frequency: Bimonthly
    • DOI: 10.7763/IJMO
    • Editor-in-Chief: Prof. Adrian Olaru
    • Executive Editor: Ms.Yoyo Y. Zhou
    • Abstracting/ Indexing: ProQuest, Crossref, Electronic Journals Library, Google Scholar, EI (INSPEC, IET), EBSCO, etc.
    • E-mail ijmo@iacsitp.com
Prof. Adrian Olaru
University Politehnica of Bucharest, Romania
I'm happy to take on the position of editor in chief of IJMO. It's a journal that shows promise of becoming a recognized journal in the area of modelling and optimization. I'll work together with the editors to help it progress.
IJMO 2011 Vol.1(3): 180-184 ISSN: 2010-3697
DOI: 10.7763/IJMO.2011.V1.32

Improving the Efficiency of Wastewater Treatment Process by Soft Computational Methods

Shahrzad Attarzadeh and Farnoosh Jalalinia

Abstract—Industrial wastewater is a major source of environment pollution and synthetic dyes are the most undesirable pollutant of the water. Wastewater treatment processes have been widely discussed in literature to find economic and safe solutions for water quality problem. In this paper, soft computing methodologies are used to model and optimize the dye removal process. Combination of Artificial Neural Networks and Genetics Algorithm results in a hybrid approach that contains advantages of each method. An Artificial Neural Network is trained using an experimental data set to approximate the relation between initial dye concentration, adsorbent, pH, and contact time as inputs and dye removal percentage as output. Genetic algorithm approach is employed to suggest the best combination of input elements to maximizing dye removal for each initial dye concentration produced by factory. This combination decreases the costs and time of the process and has economical profits for large factories.

Index Terms—Dye removal process, Artificial Neural Networks, Genetic Algorithms, optimization, wastewater treatment.

S. Attarzadeh is with the Department of Computer, Meymeh Baranch, Islamic Azad University, Meymeh, Iran (e-mail: sh_attarzadeh@iaumeymeh.ac.ir).
F. Jalalinia is with the Department of Computer, Meymeh Baranch, Islamic Azad University, Meymeh, Iran (e-mail: farnoosh.jalalinia@iaumeymeh.ac.ir).


Cite: Shahrzad Attarzadeh and Farnoosh Jalalinia, "Improving the Efficiency of Wastewater Treatment Process by Soft Computational Methods," International Journal of Modeling and Optimization vol. 1, no. 3, pp. 180-184, 2011.

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