A machine learning framework for predicting fuel consumption and CO2 emissions in hybrid and combustion vehicles: comparative analysis and performance evaluation

Rania A. Ibrahim; Nahla E. Zakzouk

doi:10.1371/journal.pone.0342418

Loading metrics

Open Access

Peer-reviewed

Research Article

A machine learning framework for predicting fuel consumption and CO₂ emissions in hybrid and combustion vehicles: comparative analysis and performance evaluation

Rania A. Ibrahim ,

Roles Investigation, Methodology, Software, Visualization, Writing – original draft

* E-mail: rania_assem@aast.edu

Affiliation Electrical and Control Engineering Department, College of Engineering and Technology, Arab Academy for Science and Technology, Alexandria, Egypt

https://orcid.org/0000-0003-3572-0190

⨯
Nahla E. Zakzouk

Roles Conceptualization, Data curation, Validation, Writing – review & editing

Affiliation Electrical and Control Engineering Department, College of Engineering and Technology, Arab Academy for Science and Technology, Alexandria, Egypt
⨯

A machine learning framework for predicting fuel consumption and CO₂ emissions in hybrid and combustion vehicles: comparative analysis and performance evaluation

Rania A. Ibrahim,
Nahla E. Zakzouk

Published: February 11, 2026
https://doi.org/10.1371/journal.pone.0342418

About the Authors

Rania A. Ibrahim

Roles Investigation, Methodology, Software, Visualization, Writing – original draft

* E-mail: rania_assem@aast.edu

Affiliation Electrical and Control Engineering Department, College of Engineering and Technology, Arab Academy for Science and Technology, Alexandria, Egypt

https://orcid.org/0000-0003-3572-0190

Nahla E. Zakzouk

Roles Conceptualization, Data curation, Validation, Writing – review & editing

Affiliation Electrical and Control Engineering Department, College of Engineering and Technology, Arab Academy for Science and Technology, Alexandria, Egypt

Competing Interests

The authors have declared that no competing interests exist.

Subject Areas
?

For more information about PLOS Subject Areas, click here.
We want your feedback. Do these Subject Areas make sense for this article? Click the target next to the incorrect Subject Area and let us know. Thanks for your help!

Fuels
Is the Subject Area "Fuels" applicable to this article?

Thanks for your feedback.
Forecasting
Is the Subject Area "Forecasting" applicable to this article?

Thanks for your feedback.
Carbon dioxide
Is the Subject Area "Carbon dioxide" applicable to this article?

Thanks for your feedback.
Algorithms
Is the Subject Area "Algorithms" applicable to this article?

Thanks for your feedback.
Linear regression analysis
Is the Subject Area "Linear regression analysis" applicable to this article?

Thanks for your feedback.
Decision tree learning
Is the Subject Area "Decision tree learning" applicable to this article?

Thanks for your feedback.
Engines
Is the Subject Area "Engines" applicable to this article?

Thanks for your feedback.
Statistical data
Is the Subject Area "Statistical data" applicable to this article?

Thanks for your feedback.