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Adaptive neural fuzzy inference (ANFI) modeling technique for production of marine biosurfactant

Abbasi, A. A ; Sharif University of Technology | 2012

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  1. Type of Document: Article
  2. DOI: 10.1115/DETC2012-70042
  3. Publisher: 2012
  4. Abstract:
  5. 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
  6. Keywords:
  7. Concentration values ; Critical medium components ; Hybrid learning algorithm ; Input variables ; Model prediction ; Modeling technique ; Statistical experimental design ; Training and testing ; Biomolecules ; Design ; Urea ; Surface active agents
  8. Source: Proceedings of the ASME Design Engineering Technical Conference ; Volume 2, Issue PARTS A AND B , 2012 , Pages 47-52 ; 9780791845011 (ISBN)
  9. URL: http://proceedings.asmedigitalcollection.asme.org/proceeding.aspx?articleid=1736138