A Comparative Study on Predicting Equivalent Noise Levels in Yanam City, Union Territory, India, using Machine Learning Models

This study indicates the utilization of two Machine learning models that is Artificial Neural Network (ANN) and Random Forest(RF), for the prediction of equivalent noise levels (Leq), across four locations covering commercial and silent zones in Yanam, Puducherry. The total Passenger Car Unit (PCU) data, observed Leq of every location was used effectively for the training and testing of the ANN model, resulting in aCoefficient of Determination (R²) value of 0.912.Additionally, a Random Forest regression model was applied for performance comparison, with a result of an R² of 0.925.The noise maps on weekdays and Sunday revealed the highest and the lowest noise levels at the locations during the 12 hour time interval. The study indicates that the noise levels are proportional to traffic volume, highlighting the need to implement effective strategies for reducing noise pollution in the area.