Energy parameter modeling in plug-in hybrid electric vehicles using supervised machine learning approaches

Energy parameter modeling in plug-in hybrid electric vehicles using supervised machine learning approaches

In this study, supervised machine learning techniques like random forest (RF), K-nearest neighbour (KNN), multiple linear regression (MLR), and artificial neural networks (ANNs) were used to predict energy parameters in plug-in hybrid electric vehicles. The primary objective of the study is to propo...

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Bibliographic Details
Main Author: Bukola Peter Adedeji
Format: Article
Language:English
Published: Elsevier 2024-06-01
Series:e-Prime: Advances in Electrical Engineering, Electronics and Energy
Subjects:
Multiple Linear Regression
Artificial Neural Networks
Random Forest
Supervised Machine Learning
Plug-in Hybrid Electric Vehicles
K-Nearest Neighbour
Online Access:http://www.sciencedirect.com/science/article/pii/S2772671124001645

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http://www.sciencedirect.com/science/article/pii/S2772671124001645

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