Prediction of equilibrium water dew point of natural gas in TEG dehydration systems using Bayesian Feedforward Artificial Neural Network (FANN)

Abstract

The aim of this paper is to predict the equilibrium water dew point of natural gas in TEG dehydration process using feedforward artificial neural network (FANN). The ANN model shows a good result as the coefficient of determination of 0.9989 and 0.9976 was obtained for training and testing data respectively with relatively small value of mean square errors of 0.0203 and 0.0221. 0.5% of average absolute deviation percentage was observed which is comparable with the literatures. It clearly shows that FANN gives a good prediction on water dew point of natural gas in TEG dehydration process.

Keywords:

• Artificial intelligent
• equilibrium water dew point
• feedforward artificial neural network
• process modeling
• TEG dehydration process

Additional information

Funding

The authors would like to acknowledge the support received from the Universiti Sains Malaysia (USM), Southern Cross University, Lismore NSW Australia and Newcastle University, United Kingdom.