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Application of artificial neural networks to predict pressure oxidative leaching of molybdenite concentrate in nitric acid media

Khoshnevisan, A ; Sharif University of Technology | 2012

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  1. Type of Document: Article
  2. DOI: 10.1080/08827508.2011.584095
  3. Publisher: Taylor and Francis Inc , 2012
  4. Abstract:
  5. This study is concerned with investigation of pressure oxidative leaching of entire molybdenum of a molybdenite concentrate. Effects of oxygen pressure, stirring speed, pulp density, acid concentration, and temperature on the leaching rate of molybdenum were studied. A three-layer feed-forward artificial neural network was applied to model the effect of the abovementioned parameters on the leaching ability. The leaching efficiency was considered as a target value for modeling. The quantified leaching efficiencies obtained by applying different parameters demonstrated a good agreement with neural network predictions
  6. Keywords:
  7. Artificial neural network ; Molybdenum ; Neural networks ; Nitric acid ; Acid concentrations ; Feed-forward artificial neural networks ; Leaching rates ; Molybdenite concentrate ; Network prediction ; Oxidative Leaching ; Oxygen pressure ; pressure leaching ; Pulp density ; Stirring speed ; Target values ; Three-layer ; Leaching
  8. Source: Mineral Processing and Extractive Metallurgy Review ; Volume 33, Issue 4 , Jul , 2012 , Pages 292-299 ; 08827508 (ISSN)
  9. URL: http://www.tandfonline.com/doi/abs/10.1080/08827508.2011.584095