Application of selected methods of computational intelligence to recognition of the liquid–gas flow regime in pipeline by use gamma absorption and frequency domain feature extraction

Author:

Hanus RobertORCID,Zych MarcinORCID,Kusy Maciej,Hossein Roshani Gholam,Nazemi Ehsan

Publisher

Elsevier BV

Reference64 articles.

1. Comparative Performance of Machine-Learning and Deep-Learning Algorithms in Predicting Gas-Liquid Flow Regimes;Hafsa;Processes,2023

2. Application of artificial neural network to multiphase flow metering: A review;Bahrami;Flow Meas. Instrum.,2024

3. Review of machine learning for hydrodynamics, transport, and reactions in multiphase flows and reactors;Zhu;Ind. Eng. Chem. Res,2022

4. Self-supervised learning-based two-phase flow regime identification using ultrasonic sensors in an S-shape riser;Kuang;Expert Syst. Appl.,2024

5. Classification of flow regimes using a neural network and a non-invasive ultrasonic sensor in an S-shaped pipeline-riser system;Nnabuife;Chem. Eng. J. Adv.,2021

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