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Prediction of wax disappearance temperature using artificial neural networks

Moradi, G ; Sharif University of Technology | 2013

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  1. Type of Document: Article
  2. DOI: 10.1016/j.petrol.2013.06.003
  3. Publisher: 2013
  4. Abstract:
  5. In this study, the artificial neural network (ANN) was used for the prediction of WDT. The inputs to network are molar mass and pressure, and the output is WDT at each input. A two-layer network with different hidden neurons and different learning algorithms such as LM, SCG, GDA and BR were examined. The network with 16 hidden neurons and Levenberg-Marquardt (LM) train function showed the best results in comparison with the other networks. Also, the predicted results of this network were compared with the thermodynamic models and better accordance with experimental data for ANN was concluded
  6. Keywords:
  7. Artificial neural network ; Hidden neurons ; Learning algorithm ; Wax disappearance temperature ; Waxy crude oil ; Experimental datum ; Levenberg-Marquardt ; Thermodynamic model ; Two-layer network ; Crude oil ; Learning algorithms ; Neurons ; Neural networks ; algorithm ; Prediction ; Wax
  8. Source: Journal of Petroleum Science and Engineering ; Volume 108 , 2013 , Pages 74-81 ; 09204105 (ISSN)
  9. URL: http://www.sciencedirect.com/science/article/pii/S0920410513001642