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Organizing, Visualizing and Understanding Households Electricity Consumption Data through Clustering Analysis.
Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.ORCID iD: 0000-0001-9947-1088
Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.ORCID iD: 0000-0003-3128-191x
2018 (English)In: Organizing, Visualizing and Understanding Households Electricity Consumption Data through Clustering Analysis, https://sites.google.com/view/arial2018/accepted-papersprogram , 2018Conference paper, Published paper (Refereed)
Abstract [en]

We propose a cluster analysis approach for organizing, visualizing and understanding households’ electricity consumption data. We initially partition the consumption data into a number of clusters with similar daily electricity consumption profiles. The centroids of each cluster can be seen as representative signatures of a household’s electricity consumption behaviors. We evaluate the proposed approach by conducting a number of experiments on electricity consumption data of ten selected households. Our results show that the approach is suitable for data analysis, understanding and creating electricity consumption behavior models.

Place, publisher, year, edition, pages
https://sites.google.com/view/arial2018/accepted-papersprogram , 2018.
National Category
Other Computer and Information Science
Identifiers
URN: urn:nbn:se:bth-17439OAI: oai:DiVA.org:bth-17439DiVA, id: diva2:1272601
Conference
2ND WORKSHOP ON AI FOR AGING, REHABILITATION AND INDEPENDENT ASSISTED LIVING (ARIAL) @IJCAI'18, Stockholm
Part of project
Bigdata@BTH- Scalable resource-efficient systems for big data analytics, Knowledge FoundationAvailable from: 2018-12-19 Created: 2018-12-19 Last updated: 2021-07-26Bibliographically approved

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fulltext(425 kB)200 downloads
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Nordahl, ChristianGrahn, HåkanPersson, MarieBoeva, Veselka

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CiteExportLink to record
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Citation style
  • apa
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