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2020 Vol.14, Issue 6 Preview Page

Research Article

December 2020. pp. 699-706
Abstract
References
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Ahn, K.U., Kim, D.W., Kim, Y.J., Yoon, S.H., Park, C.S. (2016). Issues to Be Solved for Energy Simulation of An Existing Office Building. Sustainability, 8(4), 345. 10.3390/su8040345
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Costanzo, S., Cusumano A., Giaconia, C. (2011). Ventilation rates and unsatisfied percentage from indoor CO2 concentration. Indoor Built Environment, 20(2), 232-245. 10.1177/1420326X10373330
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Jovanović, R.Ž., Sretenović, A.A., Živković, B.D. (2015). Ensemble of various neural networks for prediction of heating energy consumption. Energy and Buildings, 94, 189-199. 10.1016/j.enbuild.2015.02.052
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Ra, S.J., Shin, H.S., Suh, W.J., Chu, H.G., Park, C.S. (2017). Five Machine Learning Models for HVAC Systems in an Existing Office Building. Journal of The Architectural Institute of Korea Structure & Construction, 33(10), 69-77.
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Shin, H.S., Suh, W.J., Chu, H.G., Ra, S.J., Park, C.S. (2017). Machine Learning Models for Prediction and Control of an Ice Thermal Storage System in an Existing Building. Journal of The Architectural Institute of Korea Structure & Construction, 33(11), 63-70. 10.5659/JAIK_SC.2017.33.4.63
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Shin, K.J., Kim, H.J., Cho, Y.H. (2016). A study of the Prediction Model of Indoor Carbon Dioxide Concentrations. Journal of Korean Institute of Architectural Sustainable Environment and Building Systems, 10(1), 83-89.
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Taylor, S.T. (2006). CO2-based DCV using 62.1-2004. ASHRAE Journal, 48(5), 67-75. 10.1016/S0040-4020(06)01650-4
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Information
  • Publisher :Korean Institute of Architectural Sustainable Environment and Building Systems
  • Publisher(Ko) :한국건축친환경설비학회
  • Journal Title :Journal of Korean Institute of Architectural Sustainable Environment and Building Systems
  • Journal Title(Ko) :한국건축친환경설비학회 논문집
  • Volume : 14
  • No :6
  • Pages :699-706
  • Received Date :2020. 10. 28
  • Revised Date :2020. 11. 20
  • Accepted Date : 2020. 11. 23
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