Electric Vehicle (EV) Price Prediction using Machine Learning | Python Final Year IEEE Project 2025
Electric Vehicle (EV) Price Prediction using Machine Learning | Python Final Year IEEE Project 2024 - 2025.
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🔗Email: [email protected],
🌐Website: https://www.jpinfotech.org
📌Project Title: Electric Vehicle (EV) Price Prediction using Machine Learning.
💡Implementation: Python.
🔬Algorithm / Model Used: Gradient Boosting Regressor, Extratree Regressor.
🌐Web Framework: Flask.
🖥️Frontend: HTML, CSS, JavaScript.
💰Cost (In Indian Rupees): Rs.3000/
📘Project Abstract:
The rapid adoption of electric vehicles (EVs) is reshaping the automotive industry, driven by technological advancements and growing environmental concerns. This project, titled "Electric Vehicle (EV) Price Prediction using Machine Learning," leverages advanced regression models to predict EV prices based on a comprehensive set of features. Utilizing Python as the backend coding language and deploying the solution through a Flask-based web framework with a user-friendly front end comprising HTML, CSS, and JavaScript, the project integrates advanced machine learning techniques to achieve accurate price predictions.
The study employs two robust regression models: GradientBoostingRegressor and ExtraTreeRegressor. The GradientBoostingRegressor achieved a Training Set Mean Absolute Error (MAE) of 0.1917 and a Test Set MAE of 1.4731, while the ExtraTreeRegressor achieved a perfect Training Set MAE of 0.000 and a Test Set MAE of 1.6941.
📌IEEE Base Paper Title: Analysis and prediction of electric vehicle costs: A machine learning-based approach.
📌REFERENCE:
Abdelfetah Ouadah, Belgacem Said Khaldi, Abdelhamid Iratni, Ahmed Hafaifa, “Analysis and prediction of electric vehicle costs: A machine learning-based approach”, 2024 ASU International Conference in Emerging Technologies for Sustainability and Intelligent Systems (ICETSIS), IEEE Conference, 2024.
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