Fuel consumption through the lens of machine learning
Date
2025-12-16
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Language
English
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Abstract
Predicting fuel consumption accurately in the real world is crucial for both individual consumers, fleet directors, and policy makers to reduce costs and environmental impact. [...]
Keywords
Machine learning, fuel consumption, XGBoost, random forest, neural network, artificial intelligence, deep neural networks, ensemble models
Document Type
Master thesis
Publisher Version
Dataset
Citation
Pinto, T. (2025). Fuel consumption through the lens of machine learning [Dissertação de Mestrado em Ciência de Dados, Universidade Portucalense]. Repositório Institucional UPT. https://hdl.handle.net/11328/6860
Identifiers
TID
Designation
Mestrado em Ciência de Dados
Access Type
Open Access