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머신러닝 앙상블을 활용한 공압기의 전력 효율 최적화 시뮬레이션
김주헌 ( Juhyeon Kim ),장문수 ( Moonsoo Jang ),최지은 ( Jieun Choi ),허요섭 ( Yoseob Heo ),정현상 ( Hyunsang Chung ),박소영 ( Soyoung Park ) 한국산업융합학회 2023 한국산업융합학회 논문집 Vol.26 No.6
This study delves into methods for enhancing the power efficiency of air compressor systems, with the primary objective of significantly impacting industrial energy consumption and environmental preservation. The paper scrutinizes Shinhan Airro Co., Ltd.'s power efficiency optimization technology and employs machine learning ensemble models to simulate power efficiency optimization. The results indicate that Shinhan Airro's optimization system led to a notable 23.5% increase in power efficiency. Nonetheless, the study's simulations, utilizing machine learning ensemble techniques, reveal the potential for a further 51.3% increase in power efficiency. By continually exploring and advancing these methodologies, this research introduces a practical approach for identifying optimization points through data-driven simulations using machine learning ensembles.