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dc.contributor.authorWang, Yan
dc.contributor.authorOjleska, Vesna M.
dc.contributor.authorJing, Yuanwei
dc.contributor.authorGugulovska, Tatyana D. K.
dc.contributor.authorDimirovski, Georgi M.
dc.date.accessioned2016-02-04T12:32:40Z
dc.date.available2016-02-04T12:32:40Z
dc.date.issued2010-09
dc.identifier.citationWang, Y., Ojleska, V. M., Jing, Y., Gugulovska, T. D. K., & Dimirovski, G. M. (2010). Short term load forecasting: A dynamic neural network based genetic algorithm optimization. In 2010 14th International Power Electronics and Motion Control Conference (EPE/PEMC) (pp. T6-157-T6-161). Piscataway, NJ: IEEE. https://dx.doi.org/10.1109/EPEPEMC.2010.5606508en_US
dc.identifier.isbn9781424478569
dc.identifier.other11613502 (INSPEC)
dc.identifier.other5606508 (Scopus)
dc.identifier.urihttps://dx.doi.org/10.1109/EPEPEMC.2010.5606508
dc.identifier.urihttps://hdl.handle.net/11376/2372
dc.descriptionDimirovski, Georgi M. (Dogus Author) -- Conference full title: 2010 14th International Power Electronics and Motion Control Conference (EPE/PEMC 2010) : Ohrid, Macedonia, 6 - 8 September 2010en_US
dc.description.abstractThe short term load forecasting plays a significant role in the management of power system supply for countries and regions, in particular in cases of insufficient electric energy for increased needs. A back-propagation artificial neural-network (BP-ANN) genetic algorithm (GA) based optimizing technique for improved accuracy of predictions short term loads is proposed. With GA's optimizing and BP-ANN's dynamic capacity, the weighted GA optimization is realized by selection, crossing and mutation operations. The performance of the proposed technique has been tested using load time-series from a real-world electrical power system. Its prediction has been compared to those of obtained by only backpropagation based neural-network techniques. Simulation results demonstrated that the here proposed technique possesses superior performance thus guarantees better forecasting.en_US
dc.description.sponsorshipELEM, Repub. Macedonia Chamb. Certif. Archit. Certif. Eng.en_US
dc.language.isoengen_US
dc.publisherIEEEen_US
dc.identifier.doi10.1109/EPEPEMC.2010.5606508en_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectDistribution of Electrical Energyen_US
dc.subjectEmerging Technologyen_US
dc.subjectEnergy System Managementen_US
dc.subjectGenetic Algorithmen_US
dc.subjectModelingen_US
dc.subjectNeural Networken_US
dc.titleShort term load forecasting: A dynamic neural network based genetic algorithm optimizationen_US
dc.typeconferenceObjecten_US
dc.relation.journal2010 14th International Power Electronics and Motion Control Conference (EPE/PEMC)en_US
dc.departmentDoğuş Üniversitesi, Mühendislik Fakültesi, Kontrol ve Otomasyon Mühendisliği Bölümüen_US
dc.identifier.startpageT6-157en_US
dc.identifier.endpageT6-161en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.institutionauthorDimirovski, Georgi M.


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