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논문검색

Human-Machine Interaction Technology (HIT)

Prediction of changes in fine dust concentration using LSTM model

초록

영어

Because fine dust (PM10) has a close effect on the environment, fine dust generated in the climate and living environment has a bad effect on the human body. In this study, the LSTM model was applied to predict and analyze the effect of fine dust on Gwangju Metropolitan City in Korea. This paper uses prediction values of input variables selected through correlation analysis to confirm fine dust prediction performance. In this paper, data from the Gwangju Metropolitan City area were collected to measure fine dust. The collection period is one year’s worth of data was used from january to December of 2021, and the test data was conducted using three-month data from January to March of 2022. As a result of this study, in the as a result of predicting fine dust (PH10) and ultrafine dust (PH2.5) using the LSTM model, the RMSE was 4.61 and the test result value was as low as 4.37. This reason is judged to be the result of the contents of the oneyear sample.

목차

Abstract
1. Introduction
2. Correlation Analysis of Meteorological and Air Pollutants and Fine Dust Concentration
3. Composition of data set
4. Model design and Implementation
5. Conclusion
References

저자정보

  • Gi-Seok Lee Representative, Uclab Inc, Gwangju, Korea
  • Sang-Hyun Lee Associate Professor, Department of Computer Engineering, Honam University, Korea

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