Assessment of Air Pollutants of Dhanbad Using Machine Learning Techniques
Keywords:
Machine learning models, air quality, air pollutants, CPCB, data preprocessing, performance criteriaAbstract
A comprehensive assessment of air pollution in Dhanbad for the months of April 2019 through March 2023 was conducted using a support vector machines. random forest, xgboost, and decision tree methods in relation to seven main pollutants into the air (PM10, NO, NO2, NH3, SO2, CO, and O3). A randomly selected 30-day period was used to create line and bar graphs using accuracy & error matrices for 7 pollutants in various models. Our investigation found that the Random Forest model estimates Dhanbad air contaminants with the lowest MAE.Among the aforementioned models, the Random Forest one stands head and shoulders above the others.
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