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

被引：8

作者：

Ahmad, Z. ^{[1
]}

Bahadori, Alireza ^{[2
]}

Zhang, Jie ^{[3
]}

机构：

[1] Univ Sains Malaysia, Sch Chem Engn, Engn Campus, Nibong Tebal 14300, Penang, Malaysia

[2] Southern Cross Univ, Sch Environm Sci & Engn, Lismore, NSW, Australia

[3] Newcastle Univ, Sch Chem Engn & Adv Mat, Newcastle Upon Tyne, Tyne & Wear, England

来源：

PETROLEUM SCIENCE AND TECHNOLOGY | 2018年 / 36卷 / 20期

关键词：

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

D O I：

10.1080/10916466.2018.1496108

中图分类号：

TE [石油、天然气工业]; TK [能源与动力工程];

学科分类号：

0807 ; 0820 ;

摘要：

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.

引用

页码：1620 / 1626

页数：7

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