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°Ç¹° ¿¡³ÊÁö ºÐ¾ßÀÇ µ¥ÀÌÅÍ ºÐ¼® ±â¹ý¿¡ ´ëÇÑ °íÂû / A Review on the Data Analytics Application in Building Energy / ±¸µÎ¹ßÇ¥ - 20.¿¡³ÊÁöÀý¾à |
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ÃÖ¼±±Ô(Sun Kyu Choi) ; ¹ÚÁø¼®(Jin Seok Park) ; ÀÌÁßÀ±(Jung Yun Lee) ; °øµ¿¼®(Dong Seok Kong) ; ÇãÁ¤È£(Jung Ho Huh) |
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´ëÇѼ³ºñ°øÇÐȸ 2017³âµµ ÇϰèÇмú¹ßÇ¥´ëȸ (2017-06) |
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½ÃÀÛÆäÀÌÁö(99) ÃÑÆäÀÌÁö(4) |
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µ¥ÀÌÅͰúÇÐ ; °Ç¹°¿¡³ÊÁö°ü¸®½Ã½ºÅÛ ; ±â°èÇнÀ ; »ç¹°ÀÎÅÍ³Ý ; Data science ; Building Energy Management System ; Machine Learning ; Internet of things |
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As part of global efforts to response climate change and reduce carbon emissions, various efforts have been made to reduce energy consumption, and recently many efforts to improve energy efficiency using science and technology have been paid much attention to. In the area of energy efficiency improvement, data science will play an important role in generating timely insights so that PDCA activities(Plan-Do-Check-Action) for energy savings can be performed quickly. In this study, we will analyze what kind of data science techniques are utilized for improving energy efficiency of various facilities with what purpose, and discuss what should be considered when conducting analysis. |