Forecasting and Trend Analysis of Electric Vehicle Sales Energy Consumption and Oil Displacement in the European region using machine learning
Authors
Shiras, Muhammed
Issue Date
2025.17.12
Degree
Master of Business Administration
Publisher
Dublin Business School
Rights holder
Rights
Open Access
Abstract
The adoption of Electric Vehicles(EVs) is rapidly increasing around the world. Europe is a major region in the world which has a lot of importance .The trend of adopting EVs is also prevalent in Europe. If forecasting related to EVs can be done in Europe then government bodies in Europe will be able to get a better understanding of the scenario related to EVs. In the study proposed here, a machine learning based model for the prediction EV sales, oil displacement, and electricity consumption by EVs is built. The dataset containing data associated with EVs was used in the study. The data was used for generating visual plots for finding patterns and trends. The Voting Regressor, LSTM, Prophet, ARIMA and SARIMA models were used in the study. The Voting Regressor contained the Random Forest(RF) and Linear Regression, and the prediction by these models were used. The models were trained using the data associated with EVs in the dataset. The results of the study showed that the models were able to successfully forecast EV sales, oil displacement, and electricity consumption. Based on the performance metrics associated with the models it was seen that the best performance in prediction was shown by Voting Regressor for the prediction of EV sales and electricity consumption. ARIMA model for the prediction of the oil displacement