Prediction of Second Hand Car Prices in Sri Lanka Using Machine Learning Algorithms

Abstract

"This study aims to analyze the factors that affect the prices of second-hand cars in Sri Lanka. The study uses a regression model to identify the variables that have a significant impact on car prices, including the year of the vehicle, mileage, brand, model, fuel type, transmission, and other features. The results suggest that the year, mileage, and brand of the car have a strong impact on the prices of second-hand cars in Sri Lanka. Additionally, the study finds that cars with automatic transmission tend to have higher prices. This research contributes to the understanding of the second-hand car market in Sri Lanka and provides valuable insights for buyers and sellers in the industry.

The aim of this project is to develop a machine learning model for predicting second-hand car prices in Sri Lanka. The study will involve collecting data on various car features, such as make, model, year, mileage, engine size, fuel type, and transmission, from various online sources. A novel algorithm which has been designed will be applied to train the model and predict car prices.

The accuracy and performance of the model will be evaluated using various metrics such as mean squared error, mean absolute error, and R-squared. The outcome of this study can help used car buyers and sellers in Sri Lanka by providing them with reliable and accurate price predictions, making the car buying and selling process more efficient and informed."