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

Lookup NU author(s): Dr Jie ZhangORCiD



This is the authors' accepted manuscript of an article that has been published in its final definitive form by Taylor & Francis Inc., 2018.

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The aim of this paper is to predict the equilibrium water dew point of naturalgas in TEG dehydration process using feedforward artificial neural network(FANN). The ANN model shows a good result as the coefficient ofdetermination of 0.9989 and 0.9976 was obtained for training and testingdata respectively with relatively small value of mean square errors of0.0203 and 0.0221. 0.5% of average absolute deviation percentage wasobserved which is comparable with the literatures. It clearly shows thatFANN gives a good prediction on water dew point of natural gas in TEGdehydration process.

Publication metadata

Author(s): Ahmad Z, Bahadori A, Zhang J

Publication type: Article

Publication status: Published

Journal: Petroleum Science and Technology

Year: 2018

Volume: 36

Issue: 20

Pages: 1620-1626

Print publication date: 01/10/2018

Online publication date: 17/08/2018

Acceptance date: 01/08/2018

Date deposited: 12/10/2018

ISSN (print): 1091-6466

ISSN (electronic): 1532-2459

Publisher: Taylor & Francis Inc.


DOI: 10.1080/10916466.2018.1496108


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