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학술대회 Correlation Analysis of Usage Pattern in Home Appliance with Boosting Algorithm
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이좌형, 도윤미, 허태욱
International Conference on Information and Communication Technology Convergence (ICTC) 2022, pp.2326-2329
22PR1500, 에너지다소비 업종대상 맞춤형 공장에너지관리시스템(FEMS) 기술 개발 및 실증, 도윤미
Energy consumption in the home increases recently due to the extremely hot or cold weather. Because of COVID 19, many people stay in the home and energy consumption in the home is increasing very much. Moreover, many homes are using new electric home appliances such as dishwasher or washer dryer which consumes much electric energy for a long duration. To reduce electric energy consumption and use energy more efficiently, the usage pattern of the home appliance should be analyzed. In the paper, we propose a pattern analysis method of the home appliance using Boosting technique. Boosting method is a sort of ensemble machine learning algorithm and is based on the decision tree. The correlation between home appliance usage can be analyzed with the result of feature importance in boosting algorithm. To verify the method, we analyzed the electric usage record in the UK with boosting algorithm.
KSP 제안 키워드
Analysis method, Boosting algorithm, Cold weather, Correlation Analysis, Decision Tree(DT), Ensemble machine learning, Feature Importance, Machine Learning Algorithms, Usage Record, boosting method, boosting technique