Forecast the road accidents in Malaysia using exponential smoothing and multiple linear regression modelling / Nor Salam Abdul Manaf

In Malaysia, traffic accidents are a significant public health issue, and the government is continuously seeking for measures to prevent them. Creating precise forecasting algorithms that can anticipate future traffic accidents is one method to do this. In this study, multiple linear regression and exponential smoothing as two forecasting models examined. A straightforward forecasting methodology called exponential smoothing uses historical data to forecast future values. The concept is predicated on the idea that recent data points are more significant than historical data points. Multiple independent variables are used in a more intricate forecasting model called multiple linear regression to predict a dependent variable.