Please use this identifier to cite or link to this item: https://dspace.ncfu.ru/handle/20.500.12258/25238
Title: Comparative Analysis of Methods and Algorithms for Building a Digital Twin of a Smart City
Authors: Lutsenko, V. V.
Луценко, В. В.
Babenko, M. G.
Бабенко, М. Г.
Keywords: Big data;Smart city;Data mining;Digital twin;Neural networks
Issue Date: 2023
Citation: Lutsenko, V., Babenko, M. Comparative Analysis of Methods and Algorithms for Building a Digital Twin of a Smart City // Lecture Notes in Networks and Systems. - 2023. - 702 LNNS, pp. 277-287. - DOI: 10.1007/978-3-031-34127-4_27
Series/Report no.: Lecture Notes in Networks and Systems
Abstract: With the development of next-generation information technologies, especially big data and digital twins, the topic of building smart cities is increasingly dominating discussions about social change and economic performance. The purpose of this article is to analyze methods for building digital twins of a smart city. The paper describes the concepts underlying digital twins. Examples of the implementations of methods for building digital twins are investigated. Advantages of data mining and neural network modeling over other methods in the context of the considered characteristics are revealed. Based on the comparative analysis, it is shown that all methods can be complementary, as they are aimed to optimize processes, as well as predict and analyze problems.
URI: http://hdl.handle.net/20.500.12258/25238
Appears in Collections:Статьи, проиндексированные в SCOPUS, WOS

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