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NTIS 바로가기신재생에너지 = New & Renewable Energy, v.18 no.2, 2022년, pp.18 - 25
박래진 (Department of Electrical Engineering, Hanbat National University) , 강성우 (Department of Electrical Engineering, Korea University) , 이재형 (Korea Electric Power Corporation) , 정승민 (Department of Electrical Engineering, Hanbat National University)
In this study, we propose a wind power generation prediction system that applies machine learning and data mining to predict wind power generation. This system increases the utilization rate of new and renewable energy sources. For time-series data, the data set was established by measuring wind spe...
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