LSTM-NEURAL NETWORKS FOR CLASSIFICATION OF THE AIR QUALITY INDEX OF BISHKEK CITY
Keywords:
classification, forecast, air quality index, LSTM-neural networkAbstract
The problem of forecasting the air quality index AQI in Bishkek, depending on meteorological parameters, is considered as a task of neural network classification. The choice of the LSTM neural network as the most effective is justified. A classifier of the air quality index has been developed to solve the problem of forecasting the AQI classes “Good” / “Unhealthy” for a different history of observations of meteorological parameters and different forecast depths. A forecast accuracy of more than 90% has been achieved
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