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Adaptive Neural Fuzzy Inference (ANFI) Modeling Technique for Production of Marine Biosurfactant

[+] Author Affiliations
Ali A. Abbasi, M. T. Ahmadian

Sharif University of Technology, Tehran, Iran

Paper No. DETC2012-70042, pp. 47-52; 6 pages
doi:10.1115/DETC2012-70042
From:
  • ASME 2012 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference
  • Volume 2: 32nd Computers and Information in Engineering Conference, Parts A and B
  • Chicago, Illinois, USA, August 12–15, 2012
  • Conference Sponsors: Design Engineering Division, Computers and Information in Engineering Division
  • ISBN: 978-0-7918-4501-1
  • Copyright © 2012 by ASME

abstract

In this study; a Sugeno type ANFI model which describes the relationship between the bio surfactant concentration as a model output and the critical medium components as its inputs has been constructed. The critical medium components are glucose, urea, SrCl2 and MgSo4. The experimental data for training and testing capability of the model obtained by a statistical experimental design which have been captured from literatures. Six generalized bell shaped membership function have been selected for each of input variables and based on the training data ANFI model has been trained using the hybrid learning algorithm. The yielded biosurfactant concentration values from the model prediction shows close agreement with the experimental data.

Copyright © 2012 by ASME

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