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Performance Evaluation of an Indoor Temperature Forecasting Model based on GRU for Floor Heating System Operation
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바닥 난방 시스템 운영에 따른 GRU 기반의 실내온도 예측모델의 성능 평가

논문 기본 정보

Type
Academic journal
Author
Myeung Hun Lee (단국대학교) Young Ran Yoon (단국대학교) Hyeun Jun Moon (단국대학교)
Journal
The Korean Society of Living Environmental System Journal of The Korean Society of Living Environmental System Vol.27 No.3 KCI Accredited Journals
Published
2020.6
Pages
272 - 282 (11page)
DOI
10.21086/ksles.2020.06.27.3.272

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Performance Evaluation of an Indoor Temperature Forecasting Model based on GRU for Floor Heating System Operation
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Abstract· Keywords

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Forecasting of indoor temperature can be used to satisfy the thermal comfort and reduce energy consumption in buildings. In this study, we proposed a GRU-based model for forecasting the indoor temperature. The objective of this study is to assess the forecasting performance and transfer learning potential of GRU model in forecasting the indoor temperature, the performance is verified by comparing the LSTM model based on ground truth data. As a result, the proposed GRU model outperformed the LSTM model in forecasting the indoor temperature. The potential for transfer learning also appears to be high, these results show the potential of GRU model presented in this study for forecasting the indoor temperature.
#Indoor temperature #Forecasting model #Machine learning #Gated Recurrent Unit #Transfer learning

Contents

Abstract
1. 서론
2. 연구 방법
3. 실내온도 예측모델 개발
4. 실험 및 결과
5. 결론
REFERENCES

References (26)

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Afroz, Z. / 2018 / Real-time prediction model for indoor temperature in a commercial building / Applied Energy 231:29~53 google schola Chai, T / 2014 / Root mean square error (RMSE) or mean absolute error (MAE)?–Arguments against avoiding RMSE in the literature / Geoscientific Model Development 7(3):1247~1250 google schola Chen, T. Y. / 2002 / Application of adaptive predictive control to a floor heating system with a large thermal lag / Energy and Buildings 34(1):45~51 google schola Chen, Y. / 2020 / Transfer learning with deep neural networks for model predictive control of HVAC and natural ventilation in smart buildings / Journal of Cleaner Production 254:119866 google schola Cho, K. / 2014 / Learning phrase representations using RNN encoder-decoder for statistical machine translation google schola

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