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Utilization of least square support vector machine (LSSVM) for electrical resistivity prediction of the zn-mn-s nanocrystalline semiconductor films

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

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  1. Type of Document: Article
  2. DOI: 10.1115/IMECE2012-85028
  3. Publisher: 2012
  4. Abstract:
  5. In this investigation, application of the least square support vector machine (LSSVM) for modeling of the electrical resistivity of the magnetic Zn-Mn-S nanocrystalline semiconductor films has been described. The model has been trained based on the experimental data obtained from a published work by Sreekantha Reddy et al. The model inputs are temperature and variations in the concentrations of Zn, Mn. The results indicate that LSSVM is able to be used for accurate prediction of the electrical resistivity of the Zn-Mn-S nanocrystalline semiconductor films
  6. Keywords:
  7. Accurate prediction ; Least square support vector machines ; Model inputs ; Nanocrystalline semiconductors ; Manganese ; Mechanical engineering ; Zinc ; Electric conductivity
  8. Source: ASME International Mechanical Engineering Congress and Exposition, Proceedings (IMECE) ; Volume 3, Issue PARTS A, B, AND C , 2012 , Pages 1099-1104 ; 9780791845196 (ISBN)
  9. URL: http://proceedings.asmedigitalcollection.asme.org/proceeding.aspx?articleid=1750509