Predicting soot formation in fossil fuels: A comparative study of regression and machine learning models-Reference-Cited by-同舟云学术

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Predicting soot formation in fossil fuels: A comparative study of regression and machine learning models

Published:2024-09 Issue: Volume:12 Page:100172
ISSN:2772-5081
Container-title:Digital Chemical Engineering
language:en
Short-container-title:Digital Chemical Engineering

Author:

Lawal Ridhwan^ORCID,Farooq Wasif,Abdulraheem Abdulazeez^ORCID,Abdul Jameel Abdul Gani

Publisher

Elsevier BV

Reference75 articles.

1. Predicting sooting propensity of oxygenated fuels using artificial neural networks;Abdul Jameel;Processes,2021

2. Heavy fuel oil pyrolysis and combustion: kinetics and evolved gases investigated by TGA-FTIR;Abdul Jameel;Anal. Appl. Pyrol.,2017

3. Predicting fuel ignition quality using 1H NMR spectroscopy and multiple linear regression;Abdul Jameel;Energy Fuel.,2016

4. A minimalist functional group (MFG) approach for surrogate fuel formulation;Abdul Jameel;Combust. Flame,2018

5. Predicting octane number using nuclear magnetic resonance spectroscopy and artificial neural networks;Abdul Jameel;Energy Fuel.,2018

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