Estimating the Saturation Thermodynamic Properties of Propene Using a Feed Forward Neural Network

نویسندگان

  • Setareh Sheikh
  • Morteza Bagherpour
چکیده

A feed forward neural network model is applied to forecast the saturation thermodynamic properties of propene. The method has been used to estimate thermodynamic properties including the heat capacity, Joule-Thomson coefficient, viscosity, thermal conductivity and surface tension. Conducted experimental investigations show applicability of the proposed approach. Comparing with other theoretical models, this method is both simple and reliable. This will cause to open some potential research areas in order to avoid doing costly and some unnecessary experimental works.

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تاریخ انتشار 2013