Analysis of modern approaches for the prediction of electric energy consumption

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	2024-12-06T04:27:01Z
dc.date.available	2024-12-06T04:27:01Z
dc.date.issued	2020
dc.identifier.issn	2629-4877
dc.identifier.other	doi.org/10.1515/eng-2020-0028
dc.identifier.uri	http://rep.enu.kz/handle/enu/19911
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