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Prediction of variables involved in TEG Dehydration using hybrid models based on boosting algorithms

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成果类型:
期刊论文
作者:
Wang, Fangxiu;Zhao, Jiemei;Van Hoang, Vo
通讯作者:
Wang, FX
作者机构:
[Wang, Fangxiu; Wang, FX; Zhao, Jiemei] Wuhan Polytech Univ, Sch Math & Comp Sci, Wuhan 430023, Hubei, Peoples R China.
[Van Hoang, Vo] Bialystok Tech Univ, Fac Elect Engn, Wiejska 45C, PL-15531 Bialystok, Poland.
通讯机构:
[Wang, FX ] W
Wuhan Polytech Univ, Sch Math & Comp Sci, Wuhan 430023, Hubei, Peoples R China.
语种:
英文
关键词:
Tri ethylene glycol;Hybrid Boosting;XGBoost;Arithmetic optimization algorithm;Dehydration
期刊:
Computers & Chemical Engineering
ISSN:
0098-1354
年:
2024
卷:
188
页码:
108747
机构署名:
本校为第一且通讯机构
院系归属:
数学与计算机学院
摘要:
The extraction of gas from fields often involves impurities, necessitating natural gas processing to separate these impurities. This process typically entails the removal of acid gases (such as carbon dioxide and hydrogen sulfide) and dehydration, commonly achieved through absorption using triethylene glycol (TEG). Efforts to minimize BTEX emissions and maintain optimal dry gas water content are pivotal for enhancing the economic and environmental sustainability of natural gas processing. In this study, the accurate prediction of BTEX and dry gas water contents is aimed by boosting-based metho...

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