10.1007/s40097-016-0211-4

Neuro-fuzzy modeling to adsorptive performance of magnetic chitosan nanocomposite

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  • Bahareh Tanhaei*1,
  • Morteza Esfandyari2,
  • Ali Ayati3,
  • Mika Sillanpää4,
  1. Department of Chemical Engineering, Quchan University of Advanced Technology, Quchan, IR
  2. Department of Chemical Engineering, Faculty of Engineering, University of Bojnord, Bojnord, IR
  3. Department of Chemical Engineering, Quchan University of Advanced Technology, Quchan, IR Laboratory of Green Chemistry, LUT School of Engineering Science, Lappeenranta University of Technology, Mikkeli, 50130, FI
  4. Laboratory of Green Chemistry, LUT School of Engineering Science, Lappeenranta University of Technology, Mikkeli, 50130, FI Department of Civil and Environmental Engineering, Florida International University, Miami, 33174, US
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Published in Issue 23-11-2016

How to Cite

Tanhaei, B., Esfandyari, M., Ayati, A., & Sillanpää, M. (2016). Neuro-fuzzy modeling to adsorptive performance of magnetic chitosan nanocomposite. Journal of Nanostructure in Chemistry, 7(1 (March 2017). https://doi.org/10.1007/s40097-016-0211-4
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Abstract

Abstract In the present paper, the adaptive neural fuzzy inference system (ANFIS) was used for modeling of magnetic chitosan adsorption performance for the methyl orange removal. The ANFIS network, which is the best in data predicting, was trained with back propagation optimum method. Our results revealed that the developed ANFIS models can effectively model the non-linearity behavior of the adsorptive performance and the predicted values were in good agreement with the experimental data.

Keywords

  • Adsorption,
  • Magnetic chitosan,
  • Modeling,
  • ANFIS
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