Resumen
Forecasting particulate matter of size less than 2.5 µm (PM2.5" role="presentation">2.52.5
2.5
) in big cities is a major challenge for scientific community. In addition to environmental impacts, these particulate matter cause various diseases, such as cardiopulmonary disease, stroke, lung cancer and even neurological disorders. Forecasting high PM2.5" role="presentation">2.52.5
2.5
events helps to raise awareness among people to take precautionary measures, such as limit outdoor activities, use masks, etc. In the future, advanced Machine Learning (ML) based PM2.5" role="presentation">2.52.5
2.5
forecasting will help to reduce the cost of sampling of PM2.5" role="presentation">2.52.5
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, such as sampler and equipment costs, which are needed to measure the concentration of particulate matter in air.