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³í¹®¸í È®·üÀû ¿¡¹Ä·¹ÀÌÅ͸¦ ÀÌ¿ëÇÑ ¿ÜÇÇ ½Ã½ºÅÛ ÃÖÀû¼³°è / Optimal Design of Glazing System using Stochastic Emulator
ÀúÀÚ¸í ±è¿µÁø½Äº°ÀúÀÚ ; ¾È±â¾ð½Äº°ÀúÀÚ ; ¹Úö¼ö½Äº°ÀúÀÚ
¹ßÇà»ç Çѱ¹°ÇÃàģȯ°æ¼³ºñÇÐȸ
¼ö·Ï»çÇ× Ãß°èÇмú¹ßÇ¥´ëȸ, 2012 (2012-10)
ÆäÀÌÁö ½ÃÀÛÆäÀÌÁö(248) ÃÑÆäÀÌÁö(4)
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ÁÖÁ¦¾î È®·üÀû ÃÖÀû¼³°è ; ºÒÈ®½Ç¼º ºÐ¼® ; °¡¿ì½Ã¾È ÇÁ·Î¼¼½º ; º£ÀÌÁö¾È Á¢±Ù ; ºôµù ½Ã¹Ä·¹ÀÌ¼Ç ; stochastic optimal design ; uncertainty analysis ; gaussian process ; Bayesian approach ; Building Simulation
¿ä¾à2 This paper addresses development of a simple and quick prediction model based on the Gaussian Stochastic Process (GASP) with a far less computation time than the dynamic whole-building simulation tools. The emulator model, which can be regarded as a surrogate model of the dynamic BPS tools, is developed using Gaussian process regression model and Bayesian approach. In this study, EnergyPlus was used to derive the emulator model. In the paper, the authors exemplify the use of the emulator for optimal design of glazing system for a given office building. In general, it requires a significant simulation run-time for stochastic optimization. In this paper, it was presented coupling of the Gaussian process regression model and an optimization routine out of MATLAB optimization toolbox. It was reported that the emulator reduces computation time significantly, produces almost identical results compared to the BPS tools.
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À̽¹Î(Lee, Seung-Min) ; ±èÁøÈ£(Kim, Jin-Ho) ; ½Å±¤¼ö(Shin, Gwang-Su) ; ±èÀÇÁ¾(Kim, Eui-Jong) - Çѱ¹°ÇÃàģȯ°æ¼³ºñÇÐȸ ³í¹®Áý : Vol.12 No.6 (201812)
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±è¿µÁø(Kim, Young-Jin) ; ¹Úö¼ö(ParkCheol-Soo) - ´ëÇѰÇÃàÇÐȸ³í¹®Áý °èȹ°è : v.30 n.7 (201407)
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Á¶ÀçÈÆ(Jo Jae-Hun) - ´ëÇѰÇÃàÇÐȸ³í¹®Áý °èȹ°è : v.26 n.10 (201010)
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