Репозиторий Dspace

Analysis of modern approaches for the prediction of electric energy consumption

Показать сокращенную информацию

dc.contributor.author Kalimoldayev, Maksat
dc.contributor.author Drozdenko, Aleksey
dc.contributor.author Koplyk, Igor
dc.contributor.author Marinich, T.
dc.contributor.author Abdildayeva, Assel
dc.contributor.author Zhukabayeva, Tamara
dc.date.accessioned 2024-10-09T06:37:37Z
dc.date.available 2024-10-09T06:37:37Z
dc.date.issued 2020
dc.identifier.issn 2629-4885
dc.identifier.other doi.org/10.1515/eng-2020-0028
dc.identifier.uri http://rep.enu.kz/handle/enu/17531
dc.description.abstract A review of modern methods of forming a mathematical model of power systems and the development of an intelligent information system for monitoring electricity consumption. The main disadvantages and advantages of the existing modeling approaches , as well as their applicability to the energy systems of Ukraine and Kazakhstan,are identified. The main factors that affect the dynamics of energy consumption are identified. A list of the main tasks that need to be implemented in order to develop algorithms for predicting electricity demand for various objects, industries and levels has been developed. ru
dc.language.iso en ru
dc.publisher De Gruyter ru
dc.relation.ispartofseries 10;:350–361
dc.subject prediction ru
dc.subject power consumption ru
dc.subject panel models ru
dc.subject autoregression models ru
dc.subject neural networks ru
dc.title Analysis of modern approaches for the prediction of electric energy consumption ru
dc.type Article ru


Файлы в этом документе

Данный элемент включен в следующие коллекции

Показать сокращенную информацию

Поиск в DSpace


Просмотр

Моя учетная запись