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 |
Files in This Item:
| File | Size | Format | |
|---|---|---|---|
| scopusresults 2705 .pdf Restricted Access | 131.92 kB | Adobe PDF | View/Open |
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