Electric vehicle energy consumption prediction using stacked generalization: An ensemble learning approach
In this paper, we present an ensemble stacked generalization (ESG) approach for better
prediction of electric vehicles (EVs) energy consumption. ESG is a weighted combination of …
prediction of electric vehicles (EVs) energy consumption. ESG is a weighted combination of …
A comparative performance of machine learning algorithm to predict electric vehicles energy consumption: A path towards sustainability
The rapid growth of transportation sector and related emissions are attracting the attention of
policymakers to ensure environmental sustainability. Therefore, the deriving factors of …
policymakers to ensure environmental sustainability. Therefore, the deriving factors of …
Ensemble machine learning-based algorithm for electric vehicle user behavior prediction
This research investigates electric vehicle (EV) charging behavior and aims to find the best
method for its prediction in order to optimize the EV charging schedule. This paper …
method for its prediction in order to optimize the EV charging schedule. This paper …
From driving behavior to energy consumption: A novel method to predict the energy consumption of electric bus
Accurate real-time energy consumption prediction of electric buses (EBs) is essential for bus
operation and management, which can effectively mitigate the driving range anxiety while …
operation and management, which can effectively mitigate the driving range anxiety while …
Prediction of electric vehicle charging duration time using ensemble machine learning algorithm and Shapley additive explanations
Electric vehicles (EVs) are the most important components of smart transportation systems.
Limited driving range, prolonged charging times, and inadequate charging infrastructure are …
Limited driving range, prolonged charging times, and inadequate charging infrastructure are …
Data-driven framework for large-scale prediction of charging energy in electric vehicles
Large-scale and high-precision predictions of the charging energy required for electric
vehicles (EVs) are essential to ensure the safety of EVs and provide reliable inputs for grid …
vehicles (EVs) are essential to ensure the safety of EVs and provide reliable inputs for grid …
Development of an energy consumption prediction model for battery electric vehicles in real-world driving: A combined approach of short-trip segment division and …
Y Pan, W Fang, W Zhang - Journal of Cleaner Production, 2023 - Elsevier
Due to the excellent energy-saving and environmental protection features, electric vehicles
(EVs) are gaining significant market penetration, especially in densely populated urban …
(EVs) are gaining significant market penetration, especially in densely populated urban …
[HTML][HTML] Multistep electric vehicle charging station occupancy prediction using hybrid LSTM neural networks
Public charging station occupancy prediction plays key importance in developing a smart
charging strategy to reduce electric vehicle (EV) operator and user inconvenience. However …
charging strategy to reduce electric vehicle (EV) operator and user inconvenience. However …
[HTML][HTML] Aggregated electric vehicle fast-charging power demand analysis and forecast based on LSTM neural network
M Chang, S Bae, G Cha, J Yoo - Sustainability, 2021 - mdpi.com
With the widespread use of electric vehicles, their charging power demand has increased
and become a significant burden on power grids. The uncoordinated deployment of electric …
and become a significant burden on power grids. The uncoordinated deployment of electric …
[HTML][HTML] Data-driven tools for building energy consumption prediction: A review
The development of data-driven building energy consumption prediction models has gained
more attention in research due to its relevance for energy planning and conservation …
more attention in research due to its relevance for energy planning and conservation …