Air Quality Index prediction using machine learning for Ahmedabad city

A machine learning approach using the support vector machine (SVM) algorithm with RBF kernel demonstrated superior accuracy in predicting air quality index (AQI) for Ahmedabad, India, compared to other SVM kernels and models like SARIMA and LSTM. This study leveraged data from the Central Pollution Control Board of India, employing advanced preprocessing techniques to enhance model performance. The findings highlight the potential of sophisticated machine learning methods in improving traffic routing and identifying critical pollutants, offering a promising tool for urban air quality management.

Maltare, N. N., & Vahora, S. (2023). Air Quality Index prediction using machine learning for Ahmedabad city. Digital Chemical Engineering, 7, 100093. https://doi.org/10.1016/j.dche.2023.100093