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Journal Article Cluster Analysis to Preprocess the Building Power Usage Data Without Domain Knowledge
Cited 4 time in scopus Share share facebook twitter linkedin kakaostory
Authors
Jongwoo Choi, Il-Woo Lee, Suk-Won Cha
Issue Date
2020-03
Citation
Journal of Electrical Engineering & Technology, v.15, no.2, pp.685-692
ISSN
1975-0102
Publisher
대한전기학회 (KIEE)
Language
English
Type
Journal Article
DOI
https://dx.doi.org/10.1007/s42835-020-00372-2
Abstract
This paper aims to provide the advantage of applying cluster analysis as a data preprocessing algorithm. Daily power usage of the office building during a year is analyzed in this study. Density-based clustering algorithm is applied in this study to find outliers of the data. Calendar day of the data is mapped on the circular time domain to consider the seasonality of power data. Optimal parameters for the data normalization and clustering is found by iterative search procedures. The result of this study found many possible outliers even without considerations for the detailed domain knowledge about the data themselves. Advanced studies such as modeling or statistical analyses can take advantage of outlier-free data from the data preprocessing.
KSP Keywords
Cluster analysis(CA), Clustering algorithm, Data Normalization, Data Preprocessing, Density-based clustering, Free Data, Iterative search, Office building, Optimal parameters, Power Usage, Power data