Forecasting Air Pollution Particulate Matter (SO۲) Using Machine Learning Regression Models in different states of America

In this paper, machine learning techniques like linear regression and polynomial regression are used to predict the concentration of so۲ in different states of America. These models were compared with the existing traditional models and perform better in predictive performance. The results show machine learning models can be efficiently used to detect the quality of air and predict the level of SO۲ in the future

Keywords:

Air pollution , SO۲ , linear regression , polynomial regression.