شماره ركورد كنفرانس :
5048
عنوان مقاله :
A NEWAPPROACH FOR ESTIMATING COMPRESSIBILITY FACTOR OF NATURAL GAS BASED ON ARTIFICIAL NEURAL NETWORK
Author/Authors :
M.R ،Nikkholgh Department of Chemical Engineering - Faculty of Engineering - Arak University - Arak - Markazi, Iran , A.R ،Moghadassi Department of Chemical Engineering - Faculty of Engineering - Arak University - Arak - Markazi, Iran , F ،Parvizian Department of Chemical Engineering - Faculty of Engineering - Arak University - Arak - Markazi, Iran
كليدواژه :
Artificial Neural Network , Compressibility factor , natural gas
عنوان كنفرانس :
ششمين كنگره بين المللي مهندسي شيمي
چكيده لاتين :
In this work, the ability of Artificial Neural Network or ANN based on back-propagation algorithm to
modeling and predicting of compressibility factor of natural gas has been investigated. The MSE
analysis based on results, are used to verifying the suggested approach. Results show, a good
agreement between experimental data and ANN predictions. An important feature of the model is its
needlessness to any theoretical knowledge or human experience during the training process. This work
clearly shows the ability of ANN on calculating z-factor for natural gas only based on the
experimental data, instead of using equations of state.
