Advanced machine learning computations for estimation of hydrogen solubility in oil samples: Model comparisons and validation-Reference-Cited by-同舟云学术

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Advanced machine learning computations for estimation of hydrogen solubility in oil samples: Model comparisons and validation

Published:2024-08 Issue: Volume:60 Page:104684
ISSN:2214-157X
Container-title:Case Studies in Thermal Engineering
language:en
Short-container-title:Case Studies in Thermal Engineering

Author:

Li Deping,Yadav Anupam,Ali Eyhab,Albaghdadi Mustafa Fahem,Bains Pardeep Singh,Naeem Youssef Ali,Ahmed Fadwa Fathallah,Alam Mohammad Mahtab,Falih Khaldoon T.,Abdulridui Hussam Abdali,Kadhum Eftikhaar Hasan,Omran Alaa A.,Elawady Ahmed

Funder

Deanship of Scientific Research, King Khalid University

Publisher

Elsevier BV

Reference29 articles.

1. Machine learning basics;Goodfellow;Deep learning,2016

2. Transfer learning Gaussian process regression surrogate model with explainability for structural reliability analysis under variation in uncertainties;Saida;Comput. Struct.,2023

3. Development of advanced machine learning models for optimization of methyl ester biofuel production from papaya oil: Gaussian process regression (GPR), multilayer perceptron (MLP), and K-nearest neighbor (KNN) regression models;Sumayli;Arab. J. Chem.,2023

4. Online feedback optimization of compressor stations with model adaptation using Gaussian process regression;Zagorowska;J. Process Control,2023

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