Published Paper Details:

The main causes of air pollution in India's metropolitan areas have been linked to urbanization and industrial expansion. Air pollution has been identified as one of the most serious issues in metropolitan areas. Particulate matter is still one of the most significant sources of air pollution in cities, and both acute and chronic exposures have major health consequences. Meteorological factors play a key role in determining the presence of particulate matter. As a result, the primary goal of this study is to examine and assess machine learning models and methods that deal with a specific field, namely Particulate Matter, as well as to determine the strengths of various machine learning techniques and give background information. This study also intends to emphasize the role of input predictors in enhancing predictive accuracy and the core methodologies of machine learning and their importance in enhancing prediction performance. This study reveals that how successful it is to combine machine learning approaches with Particulate Matter prediction.