A Temporal Approach for Air Quality Forecast

摘要: Recently, air pollution caused by particulate matter that the diameter is less than or equal to 2.5 μg/m3 has become an important issue. It so tiny it can go through alveolar microvascular and enter our body. PM2.5 makes a significant impact on human health. Therefore, monitoring forecasting quality indispensable task for society. Nowadays, we easily acquire Air Quality Indices (AQIs) installing small-scale sensor downloading from some freely authorized databases. However, people demand farther information plan their route. This research aims forecast value in future hours. Previous studies indicated varies nonlinearly urban areas depends several factors such as temperature, humidity wind speed. combine data AirBox meteorology value. continuous data. If monitored good at last time stamp, next high possibility be same location. And may have regular history We values via algorithm similar weighted average method. figure out intervals with weather condition. Finally, error calculated examine accuracy of In contrast famous method, Pearson’s Correlation Coefficient, method preforms well stable forecast.