Yurii Kravchenko
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- Cybersecurity and Information Systems 22
- Software-Defined Networks and 5G 2
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- Information Systems and Technology Applications 9
- Information Systems top 10%
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- Aerospace, Electronics, Mathematical Modeling 2
- Artificial Intelligence top 10%
- Mathematical Control Systems and Analysis 6
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- Advanced Data Processing Techniques 6
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- Military Technology and Strategies 4
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- Advanced Signal Processing Techniques 2
- Co-authors
- Олег БарабашNitza DavidovitchОлександр ЛаптєвSerge KernbachLeena KorpinenYu. M. SinyukovY. V. KhyzhniakL.V. Bravina
- Journals
- SHILAP Revista de lepidopterología (1 paper)Physica Scripta (1 paper)International Journal of Intelligent Systems and Applications (1 paper)
In The Last Decade
Yurii Kravchenko
29 papers receiving 348 citations
Peers
Comparison fields: 5 of 51
- Computer Networks and Communications 284
- Management Information Systems 109
- Information Systems 81
- Nature and Landscape Conservation 44
- Artificial Intelligence 111
Countries citing papers authored by Yurii Kravchenko
This map shows the geographic impact of Yurii Kravchenko's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Yurii Kravchenko with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yurii Kravchenko more than expected).
Fields of papers citing papers by Yurii Kravchenko
This network shows the impact of papers produced by Yurii Kravchenko. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Yurii Kravchenko. The network helps show where Yurii Kravchenko may publish in the future.
Co-authorship network
The 10 scholars most cited alongside Yurii Kravchenko, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2022 | 0 | |
| 2 | 2021 | 2 | |
| 3 | 2021 | 0 | |
| 4 | 2021 | 0 | |
| 5 | 2021 | 0 | |
| 6 | 2021 | 1 | |
| 7 | 2021 | 24 | |
| 8 | 2020 | 4 | |
| 9 | 2020 | 5 | |
| 10 | 2020 | 6 | |
| 11 | 2020 | 21 | |
| 12 | 2020 | 12 | |
| 13 | Machine Learning Algorithms for Predicting the Results of COVID-19 Coronavirus Infection. | 2020 | 1 |
| 14 | 2020 | 22 | |
| 15 | 2019 | 21 | |
| 16 | 2018 | 0 | |
| 17 | 2017 | 3 | |
| 18 | 2017 | 12 | |
| 19 | 2017 | 3 | |
| 20 | 2016 | 2 |
About Yurii Kravchenko
Yurii Kravchenko is a scholar working on Computer Networks and Communications, Management Information Systems and Control and Systems Engineering, having authored 38 papers that have together received 362 indexed citations. Recurring topics across this work include Cybersecurity and Information Systems (22 papers), Information Systems and Technology Applications (9 papers), Advanced Data Processing Techniques (6 papers), Mathematical Control Systems and Analysis (6 papers), Military Technology and Strategies (4 papers), Aerospace, Electronics, Mathematical Modeling (2 papers), Advanced Signal Processing Techniques (2 papers) and Software-Defined Networks and 5G (2 papers). The work is most often cited by research in Computer Networks and Communications (284 citations), Management Information Systems (109 citations) and Information Systems (81 citations). Yurii Kravchenko has collaborated with scholars based in Ukraine, Israel and Russia. Frequent co-authors include Олег Барабаш, Nitza Davidovitch, Олександр Лаптєв, Serge Kernbach, Leena Korpinen, Yu. M. Sinyukov, Y. V. Khyzhniak, L.V. Bravina, G. Nigmatkulov and E. Zabrodin. Their work appears in journals such as SHILAP Revista de lepidopterología, Physica Scripta and International Journal of Intelligent Systems and Applications.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.