Prediction of EV charging behavior using machine learning
As a key pillar of smart transportation in smart city applications, electric vehicles (EVs) are
becoming increasingly popular for their contribution in reducing greenhouse gas emissions …
becoming increasingly popular for their contribution in reducing greenhouse gas emissions …
[HTML][HTML] Sequential learning-based energy consumption prediction model for residential and commercial sectors
The use of electrical energy is directly proportional to the increase in global population, both
concerning growing industrialization and rising residential demand. The need to achieve a …
concerning growing industrialization and rising residential demand. The need to achieve a …
Data-driven spatial-temporal prediction of electric vehicle load profile considering charging behavior
Accurately predicting the spatial-temporal distribution of electric vehicles (EVs) load is of
great significance to the optimal dispatching and safe operation of the power grid. This …
great significance to the optimal dispatching and safe operation of the power grid. This …
Charging demand of plug-in electric vehicles: Forecasting travel behavior based on a novel rough artificial neural network approach
The market penetration of Plug-in Electric Vehicles (PEVs) is escalating due to their energy
saving and environmental benefits. In order to address PEVs impact on the electric …
saving and environmental benefits. In order to address PEVs impact on the electric …
[HTML][HTML] Short-term energy forecasting using machine-learning-based ensemble voting regression
Meeting the required amount of energy between supply and demand is indispensable for
energy manufacturers. Accordingly, electric industries have paid attention to short-term …
energy manufacturers. Accordingly, electric industries have paid attention to short-term …
Stacking Deep learning and Machine learning models for short-term energy consumption forecasting
S Reddy, S Akashdeep, R Harshvardhan… - Advanced Engineering …, 2022 - Elsevier
Accurate prediction of electricity consumption is essential for providing actionable insights to
decision-makers for managing volume and potential trends in future energy consumption for …
decision-makers for managing volume and potential trends in future energy consumption for …
Grey wolf optimizer-based machine learning algorithm to predict electric vehicle charging duration time
Precise charging time prediction can effectively mitigate the inconvenience to drivers
induced by inevitable charging behavior throughout trips. Although the effectiveness of the …
induced by inevitable charging behavior throughout trips. Although the effectiveness of the …
Prediction of electrical energy consumption based on machine learning technique
R Banik, P Das, S Ray, A Biswas - Electrical Engineering, 2021 - Springer
The forecast of electricity demand in recent years is becoming increasingly relevant because
of market deregulation and the introduction of renewable resources. To meet the emerging …
of market deregulation and the introduction of renewable resources. To meet the emerging …
[HTML][HTML] Electric vehicles survey and a multifunctional artificial neural network for predicting energy consumption in all-electric vehicles
BP Adedeji - Results in Engineering, 2023 - Elsevier
This study contains a survey on the architecture of electric vehicles and an artificial neural
network application for prediction of energy consumption in all-electric vehicles. In this study …
network application for prediction of energy consumption in all-electric vehicles. In this study …
Machine learning-based method for remaining range prediction of electric vehicles
L Zhao, W Yao, Y Wang, J Hu - Ieee Access, 2020 - ieeexplore.ieee.org
Limited driving range is one of the major obstacles to the widespread application of electric
vehicles (EVs). Accurately predicting the remaining driving range can effectively reduce the …
vehicles (EVs). Accurately predicting the remaining driving range can effectively reduce the …