Estimation of the methanol loss in the gas hydrate prevention unit using the artificial neural networks: Investigating the effect of training algorithm on the model accuracy-Reference-Cited by-同舟云学术

Estimation of the methanol loss in the gas hydrate prevention unit using the artificial neural networks: Investigating the effect of training algorithm on the model accuracy

Published:2022-04-18 Issue:6 Volume:10 Page:1902-1912
ISSN:2050-0505
Container-title:Energy Science & Engineering
language:en
Short-container-title:Energy Science & Engineering

Author:

Xu Haitao¹,Wu Xiangwei²,Khandakar Amith³^ORCID

Affiliation:

1. Civil engineering College Zhengzhou University of Technology Zhengzhou China

2. Engineering Training Center Zhengzhou University of Technology Zhengzhou China

3. Department of Electrical Engineering Qatar University Doha Qatar

Publisher

Wiley

Subject

General Energy,Safety, Risk, Reliability and Quality

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/ese3.1156

Reference70 articles.

1. Pore structure heterogeneity of Wufeng-Longmaxi shale, Sichuan Basin, China: Evidence from gas physisorption and multifractal geometries

2. Hydrocarbon reservoir model detection from pressure transient data using coupled artificial neural network—Wavelet transform approach

3. Comparison of two different flow types on CO removal along a two-stage hydrogen permselective membrane reactor for methanol synthesis

4. Improvement of online adaptation knowledge acquisition and reuse in case-based reasoning: Application to process engineering design

5. Artificial intelligence in engineering risk analytics

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