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Conference Paper
Correlation Analysis of Usage Pattern in Home Appliance with Boosting Algorithm
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- Authors
- Joa Hyoung Lee, YoonMee Doh, Tae-Wook Heo
- Issue Date
- 2022-10
- Citation
- International Conference on Information and Communication Technology Convergence (ICTC) 2022, pp.2326-2329
- Publisher
- IEEE
- Language
- English
- Type
- Conference Paper
- Abstract
- 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 Keywords
- 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