سال انتشار: ۱۳۸۸

محل انتشار: ششمین کنگره بین المللی مهندسی شیمی

تعداد صفحات: ۶

نویسنده(ها):

M.R. Nikkholgh – Department of Chemical Engineering, Faculty of Engineering, Arak University,
A.R. Moghadassi – Department of Chemical Engineering, Faculty of Engineering, Arak University,
F. Parvizian – Department of Chemical Engineering, Faculty of Engineering, Arak University,

چکیده:

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.