Recent publications
A Novel Approach for Predicting Particulate Matter 2.5 and 10 Concentration using Modal Autoformer and Seq-2Seq Model
Air Quality
Precise and dependable forecasting of Particulate Matter 2.5 ( P M 2.5 ) and P M 10 levels hold significant importance for the public's ability to proactively mitigate exposure to air pollution and for informing governmental policy responses. Nonetheless, predicting PM2.5 and PM10 concentrations...
Deep learning
adaptive Feline Optimizer
+7 more
Enhanced Deep Maxout Network for Monitoring Particulate Matter 2.5 and 10 Concentration in Air via Interpolated Data Smoothing
Air Quality
Currently, most of the global population resides in metropolitan areas, where air quality standards are not properly monitored. As a result, people are constantly exposed to air contaminants that exceed the thresholds set by the World Health Organization (WHO). Air quality monitoring system is often...
Air quality monitoring
PM concentration 2.5 and 10 forecasting
+5 more