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논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 저널정보
- 한국통계학회 CSAM(Communications for Statistical Applications and Methods) CSAM(Communications for Statistical Applications and Methods) 제27권 제6호
- 발행연도
- 2020.11
- 수록면
- 589 - 602 (14page)
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초록· 키워드
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The development of smart grids has enabled the easy collection of a large amount of power data. There are some common patterns that make it useful to cluster power consumption patterns when analyzing s power big data. In this paper, clustering analysis is based on distance functions for time series and clustering algorithms to discover patterns for power consumption data. In clustering, we use 10 distance measures to find the clusters that consider the characteristics of time series data. A simulation study is done to compare the distance measures for clustering. Cluster validity measures are also calculated and compared such as error rate, similarity index, Dunn index and silhouette values. Real power consumption data are used for clustering, with five distance measures whose performances are better than others in the simulation.
목차
Abstract
1. Introduction
2. Dissimilarity measure
3. Clustering methods
4. Data analysis
5. Discussion
References
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UCI(KEPA) : I410-ECN-0101-2023-310-001442201