@article{ART003139179},
author={Han-Sung Lee and Youngbok Cho},
title={Machine Learning-based Power Usage Abnormality Detection},
journal={Journal of The Korea Society of Computer and Information},
issn={1598-849X},
year={2024},
volume={29},
number={11},
pages={107-112},
doi={10.9708/jksci.2024.29.11.107}
TY - JOUR
AU - Han-Sung Lee
AU - Youngbok Cho
TI - Machine Learning-based Power Usage Abnormality Detection
JO - Journal of The Korea Society of Computer and Information
PY - 2024
VL - 29
IS - 11
PB - The Korean Society Of Computer And Information
SP - 107
EP - 112
SN - 1598-849X
AB - In this paper, we propose a method to detect abnormal power usage conditions in domestic franchise convenience stores, by detecting cases where the temperature of the refrigeration or freezer equipment operates outside the normal range and classifying detailed abnormal situations. Compared to normal data, abnormal data is very small, and the amount of data varies depending on the type of abnormality, leading to a data imbalance issue. The proposed method employs a hierarchical structure that combines a time series classification algorithm with kNN, addressing the data imbalance problem and enabling classification using relatively small amounts of data. In this paper, we conducted an experiment by independently constructing our own dataset to validate the proposed methodology.
KW - Anomaly detection;Time series classifier;Hierarchical machine learning;LSTM;GRU;kNN
DO - 10.9708/jksci.2024.29.11.107
ER -
Han-Sung Lee and Youngbok Cho. (2024). Machine Learning-based Power Usage Abnormality Detection. Journal of The Korea Society of Computer and Information, 29(11), 107-112.
Han-Sung Lee and Youngbok Cho. 2024, "Machine Learning-based Power Usage Abnormality Detection", Journal of The Korea Society of Computer and Information, vol.29, no.11 pp.107-112. Available from: doi:10.9708/jksci.2024.29.11.107
Han-Sung Lee, Youngbok Cho "Machine Learning-based Power Usage Abnormality Detection" Journal of The Korea Society of Computer and Information 29.11 pp.107-112 (2024) : 107.
Han-Sung Lee, Youngbok Cho. Machine Learning-based Power Usage Abnormality Detection. 2024; 29(11), 107-112. Available from: doi:10.9708/jksci.2024.29.11.107
Han-Sung Lee and Youngbok Cho. "Machine Learning-based Power Usage Abnormality Detection" Journal of The Korea Society of Computer and Information 29, no.11 (2024) : 107-112.doi: 10.9708/jksci.2024.29.11.107
Han-Sung Lee; Youngbok Cho. Machine Learning-based Power Usage Abnormality Detection. Journal of The Korea Society of Computer and Information, 29(11), 107-112. doi: 10.9708/jksci.2024.29.11.107
Han-Sung Lee; Youngbok Cho. Machine Learning-based Power Usage Abnormality Detection. Journal of The Korea Society of Computer and Information. 2024; 29(11) 107-112. doi: 10.9708/jksci.2024.29.11.107
Han-Sung Lee, Youngbok Cho. Machine Learning-based Power Usage Abnormality Detection. 2024; 29(11), 107-112. Available from: doi:10.9708/jksci.2024.29.11.107
Han-Sung Lee and Youngbok Cho. "Machine Learning-based Power Usage Abnormality Detection" Journal of The Korea Society of Computer and Information 29, no.11 (2024) : 107-112.doi: 10.9708/jksci.2024.29.11.107
