Decision Tree Based Customer Analysis Method for Energy Planning in Smart Cities

dc.contributor.authorYaman, Orhan
dc.contributor.authorYetis, Hasan
dc.contributor.authorKarakose, Mehmet
dc.date.accessioned2026-08-12T16:08:34Z
dc.date.issued2020
dc.departmentFırat Üniversitesi
dc.description2020 International Conference on Data Analytics for Business and Industry: Way Towards a Sustainable Economy, ICDABI 2020 -- 26 October 2020 through 27 October 2020 -- Sakheer -- 166670
dc.description.abstractIn this study, a method is proposed to estimate energy consumption and to plan maintenance works on energy lines according to energy consumption. In our study, energy consumption can be estimated at any time of the day by analysing parameters such as temperature, pressure, and wind using decision tree methods. For this aim, "Fine Tree", "Medium Tree"and "Coarse Tree"which are different implementations of decision trees are used. The success is 76.77% with the Fine Tree method, 76.42% with the Medium Tree method, and 73.92% with the Coarse Tree method. As a result, Energy consumption is estimated by using environmental conditions, time, day, month, and season information within the scope of the smart city. Thus, energy distribution companies can make energy planning by estimating the energy consumption of their customers. In addition, performing maintenance and repair operations on energy distribution lines in a convenient time period according to these results will increase customer satisfaction. © 2020 IEEE.
dc.description.sponsorshipFirat Üniversitesi, FU, (MF.20.25)
dc.identifier.doi10.1109/ICDABI51230.2020.9325644
dc.identifier.isbn978-172819675-6
dc.identifier.scopus2-s2.0-85100457365
dc.identifier.scopusqualityN/A
dc.identifier.urihttps://doi.org/10.1109/ICDABI51230.2020.9325644
dc.identifier.urihttps://hdl.handle.net/11508/41305
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherInstitute of Electrical and Electronics Engineers Inc.
dc.relation.ispartof2020 International Conference on Data Analytics for Business and Industry: Way Towards a Sustainable Economy, ICDABI 2020
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_Scopus_20260511
dc.subjectcustomer analysis; decision tree; energy planning; smart cities
dc.titleDecision Tree Based Customer Analysis Method for Energy Planning in Smart Cities
dc.typeConference Object

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