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Conference Paper
LSTM based Analysis of Sequential Usage Pattern for Electrical Appliance
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- Authors
- Joa Hyoung Lee, YoonMee Doh, Tae-Wook Heo
- Issue Date
- 2024-02
- Citation
- International Conference on Artificial Intelligence in Information and Communication (ICAIIC) 2024, pp.112-116
- Language
- English
- Type
- Conference Paper
- Abstract
- Electrical appliances used at home are sometimes used independently, but there are also many cases where they are sequentially used in connection with other home appliances. Home appliances used sequentially and continuously have a characteristic that consumes a lot of energy and takes a long time compared to devices used alone. In this paper, we seek a way to find the correlation between home appliances that are used sequentially in succession by using LSTM, a kind of machine learning technique. Since the LSTM has the characteristic of maintaining the past value for a long period by transferring the cell value, it is possible to determine the correlation between the data used by providing a certain interval. Using these characteristics, we tried to analyze the correlation between home appliances, which correlates with the order of use in time. To verify the method, we analyzed the electric usage record in the UK with the LSTM algorithm.
- KSP Keywords
- Electrical appliance, Home appliances, Long period, Long time, Machine Learning technique(MLT), Usage Patterns, Usage Record