Estimating water content of natural gas: A radial basis function neural network method-Reference-Cited by-同舟云学术

Estimating water content of natural gas: A radial basis function neural network method

Published:2017-09-17 Issue:18 Volume:35 Page:1852-1858
ISSN:1091-6466
Container-title:Petroleum Science and Technology
language:en
Short-container-title:Petroleum Science and Technology

Author:

Hosseini Nazhad Seyed Hossein¹,Sasanipour Jafar²,Parsaei Mohammad Reza³,Javidan Reza³,Baghban Alireza⁴

Affiliation:

1. Department of Computer Engineering, Ahar Branch, Islamic Azad University, Ahar, Iran

2. Department of Gas Engineering, Ahwaz Faculty of Petroleum Engineering, Petroleum University of Technology (PUT), Ahwaz, Iran

3. Department of Computer Engineering and Information Technology, Shiraz University of Technology, Shiraz, Iran

4. Department of Chemical Engineering, Amirkabir University of Technology, Mahshahr Campus, Mahshahr, Iran

Publisher

Informa UK Limited

Subject

Geotechnical Engineering and Engineering Geology,Energy Engineering and Power Technology,Fuel Technology,General Chemical Engineering,General Chemistry

Link

https://www.tandfonline.com/doi/pdf/10.1080/10916466.2017.1339198

Reference23 articles.

1. Evolving machine learning models to predict hydrogen sulfide solubility in the presence of various ionic liquids

2. Prediction carbon dioxide solubility in presence of various ionic liquids using computational intelligence approaches

3. Phase equilibrium modeling of semi-clathrate hydrates of seven commonly gases in the presence of TBAB ionic liquid promoter based on a low parameter connectionist technique

4. Application of LSSVM strategy to estimate asphaltene precipitation during different production processes

5. Modeling of true vapor pressure of petroleum products using ANFIS algorithm

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