The Transactions of The Korean Institute of Electrical Engineers (전기학회논문지)

The Korean Institute of Electrical Engineers (대한전기학회)
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A Practical Approach to the Real Time Prediction of PM10 for the Management of Indoor Air Quality in Subway Stations

지하철 역사 실내 공기질 관리를 위한 실용적 PM10 실시간 예측

  • Jeong, Karpjoo (Institute for Ubiquitous Information Technology and Applications, Konkuk University) ;
  • Lee, Keun-Young (Institute for Ubiquitous Information Technology and Applications, Konkuk University)
  • Received : 2016.10.31
  • Accepted : 2016.11.07
  • Published : 2016.12.01
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Abstract

The real time IAQ (Indoor Air Quality) management is very important for large buildings and underground facilities such as subways because poor IAQ is immediately harmful to human health. Such IAQ management requires monitoring, prediction and control in an integrated and real time manner. In this paper, we present three PM10 hourly prediction models for such realtime IAQ management as both Multiple Linear Regression (MLR) and Artificial Neural Network (ANN) models. Both MLR and ANN models show good performances between 0.76 and 0.88 with respect to R (correlation coefficient) between the measured and predicted values, but the MLR models outperform the corresponding ANN models with respect to RMSE (root mean square error).

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References

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