سامانه همایش های دانشگاه آزاد اسلامی واحد نجف آباد

صفحه اصلی / International Conference on Artificial Intelligence; City, Industry and Health

A Review of Machine Learning Algorithms for Urban Air Pollution Prediction

نویسندگان :

Neda Chatraei Azizabadi¹ Nasim Noorafza²

1- Islamic Azad University, Najafabad, Software Department 2- Islamic Azad University, Najafabad, Software Department

کلمات کلیدی :

Urban air pollution،machine learning algorithms،environment،machine learning

چکیده :

Air pollution is one of the most pressing environmental and public health challenges of our time, with severe adverse effects on human health. Population growth, industrialization, and increasing vehicular traffic have exacerbated greenhouse gas and particulate matter emissions, contributing to the rise in respiratory and cardiovascular diseases. Air quality prediction has emerged as a key strategy for mitigating this crisis. Machine learning, with its ability to analyze complex datasets (e.g., weather conditions, traffic patterns, and industrial activity) and identify hidden trends, offers a powerful tool for predicting pollution levels. This study reviews a range of machine learning algorithms applied to urban air pollution forecasting, aiming to provide more accurate models and actionable insights for environmental and public health policymaking. Advances in these technologies hold promise for improving air quality management and enhancing public health outcomes.