FORECASTING OF BISHKEK AIR QUALITY INDEX CLASSES ACCOUNTING FOR THE 2020-2021 PERIOD NEW DATA ON THE BASE LSTM-NETWORKS CLASSIFIER

Authors

  • Lychenko N.M. Machinery researching and Аutomatics Institute of Kyrgyz Republic National Academy of Science
  • Sorokovaya A.V. Machinery researching and Automatics Institute of Kyrgyz Republic National Academy of Sciences

Keywords:

classification, air quality index, LSTM neural network, forecast accuracy.

Abstract

Predictive models of the air quality index AQI in Bishkek have been developed based on classifiers based on the LSTM network. The models allow, depending on meteorological conditions and the previous history of AQI values, to predict the AQI class from the possible four integrated classes: AQI≤50 / 50 <AQI≤100 / 100 <AQI≤150 / AQI> 150. The forecast is possible up to 4 days ahead with an accuracy of at least 77%.

References

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FORECASTING OF BISHKEK AIR QUALITY INDEX CLASSES ACCOUNTING FOR THE 2020-2021 PERIOD NEW DATA ON THE BASE LSTM-NETWORKS CLASSIFIER

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Published

2021-07-20

Issue

Section

INFORMATION TECHNOLOGY AND INFORMATION PROCESSING

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