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dc.contributor.authorAzarov, I. V.-
dc.contributor.authorАзаров, И. В.-
dc.contributor.authorVoronkin, V. S.-
dc.contributor.authorВоронкин, В. С.-
dc.contributor.authorChaika, I. V.-
dc.contributor.authorLyurova, A.-
dc.contributor.authorЛюрова, А.-
dc.contributor.authorKotlov, M. A.-
dc.contributor.authorКотлов, М. А.-
dc.contributor.authorЧайка И. В.-
dc.date.accessioned2021-04-27T07:51:05Z-
dc.date.available2021-04-27T07:51:05Z-
dc.date.issued2021-
dc.identifier.citationAzarov, I., Voronkin, R., Chaika, I., Lyurova, A., Kotlov, M. The development of the information system for anomality detection in the utility meters data using self-organized maps // CEUR Workshop Proceedings. - 2021. - Volume 2842. - Pages 13-19ru
dc.identifier.urihttp://hdl.handle.net/20.500.12258/15841-
dc.description.abstractIn this article, a project has been developed for the modernization of the data analysis technology of the system for accounting for the consumption of utility resources. The need to improve the system is due to insufficient efficiency in identifying the facts of unaccounted consumption of utility resources. Automation of data analysis processes will be based on the development of an artificial neural network. A feedforward network based on a multilayer perceptron and consisting of 1 hidden layer was chosen as a model. The backpropagation algorithm was chosen as the method for training the neural networkru
dc.language.isoenru
dc.publisherCEUR-WSru
dc.relation.ispartofseriesCEUR Workshop Proceedings-
dc.subjectNeural networksru
dc.subjectSelf-organized map (SOM)ru
dc.subjectCommercial accountingru
dc.subjectEnergy efficiencyru
dc.subjectEnergy savingInformation systemru
dc.subjectData miningru
dc.titleThe development of the information system for anomality detection in the utility meters data using self-organized mapsru
dc.typeСтатьяru
vkr.instИнститут математики и информационных технологий имени профессора Н.И. Червяковаru
Appears in Collections:Статьи, проиндексированные в SCOPUS, WOS

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