Impact of air pollutants on climate change and prediction of air quality index using machine learning models

• Main Authors: Ravindiran G., Rajamanickam S., Kanagarathinam K., Hayder G., Janardhan G., Arunkumar P., Arunachalam S., AlObaid A.A., Warad I., Muniasamy S.K.
• Other Authors: 57226345669
• Format: Article
• Published: Academic Press Inc. 2024
• Subjects: Air pollution; Air quality index; Climate action; Machine learning; Air Pollutants; Air Pollution; Climate Change; India; Machine Learning; Chennai; Tamil Nadu; Air quality; Climate change; Climate models; Errors; Fog; Forecasting; Forestry; Higher order statistics; Learning algorithms; Mean square error; Quality assurance; 'current; Air pollutants; Air quality indices; Coastal cities; Historical data; Machine learning models; Machine-learning; Metropolitan cities; action plan; air quality; atmospheric pollution; climate change; error analysis; machine learning; particulate matter; air pollutant; air pollution; article; correlation coefficient; heat; mean absolute error; meteorology; particulate matter 2.5; prediction; random forest; root mean squared error
• Institution: Universiti Tenaga Nasional

The impact of air pollution in Chennai metropolitan city, a southern Indian coastal city was examined to predict the Air Quality Index (AQI). Regular monitoring and prediction of the Air Quality Index (AQI) are critical for combating air pollution. The current study created machine learning models s...