dr Lyudmyla Kirichenko | Institute of Mathematics

Autorstwo i redakcja książek oraz wydań specjalnych

Kirichenko, L., Pichugina, O., Radivilova, T., Pavlenko, K. Application of Wavelet Transform for Machine Learning Classification of Time Series Lecture Notes on Data Engineering and Communications Technologies, 2023, 149, pp. 547–563. Springer, Cham. https://doi.org/10.1007/978-3-031-16203-9_31
Radivilova, T., Kirichenko, L., Alghawli, A.S., Kulbachnyi, V., Bondarenko, O. Statistical and 2 Signature Analysis Methods of Intrusion Detection Lecture Notes on Data Engineering and Communications Technologie, 2022, 115, pp. 115–131. Springer, Cham. https://doi.org/10.1007/978-3-030-95161-0_5
Kirichenko, L., Radivilova, T., Ryzhanov, V. Applying Visibility Graphs to Classify Time Series Lecture Notes on Data Engineering and Communications Technologies, 2022, 77, pp. 397–409. https://doi.org/10.1007/978-3-030-82014-5_26
Kirichenko L., Zinchenko P., Radivilova T. Classification of Time Realizations Using Machine Learning Recognition of Recurrence Plots. Lecture Notes in Computational Intelligence and Decision Making. ISDMCI 2020. Advances in Intelligent Systems and Computing, 2021, vol 1246. Springer, Cham, pp. 687-696. https://doi.org/10.1007/978-3-030-54215-3_44.
Kirichenko L., Radivilova T., Bulakh V. (2020) Binary Classification of Fractal Time Series by Machine Learning Methods. In: Lytvynenko V., Babichev S., Wójcik W., Vynokurova O., Vyshemyrskaya S., Radetskaya S. (eds) Lecture Notes in Computational Intelligence and Decision Making. ISDMCI 2019. Advances in Intelligent Systems and Computing, vol 1020. Springer, Cham pp.701-711. https://doi.org/10.1007/978-3-030-26474-1_49
Kirichenko L., Radivilova T., Zinkevich I. (2018) Comparative Analysis of Conversion Series Forecasting in E-commerce Tasks. In: Shakhovska N., Stepashko V. (eds). Advances in Intelligent Systems and Computing, vol 689. Springer, Cham, pp.230-242. doi: https://doi.org/10.1007/978-3-319-70581-1_16
Radivilova T., Kirichenko L., Ageiev D., Bulakh V. (2020) The Methods to Improve Quality of Service by Accounting Secure Parameters. In: Hu Z., Petoukhov S., Dychka I., He M. (eds) Advances in Computer Science for Engineering and Education II. ICCSEEA 2019. Advances in Intelligent Systems and Computing, vol 938, pp 346-355. Springer, Cham. doi: https://doi.org/10.1007/978-3-030-16621-2_32

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Publikacje w czasopismach naukowych

Kirichenko L, Lavrynenko R. Probabilistic Machine Learning Methods for Fractional Brownian Motion Time Series Forecasting. Fractal and Fractional. 2023; 7(7):517. https://doi.org/10.3390/fractalfract7070517
Kirichenko, Lyudmyla, Tamara Radivilova, Bohdan Sydorenko, and Sergiy Yakovlev. Detection of Shoplifting on Video Using a Hybrid Network. Computation 2022, 10, 199. https://doi.org /10.3390/computation10110199
Lyudmyla Kirichenko, Abed Saif Ahmed Alghawli, Tamara Radivilova. Generalized Approach to Analysis of Multifractal Properties from Short Time Series. International Journal of Advanced Computer Science and Applications(IJACSA), Volume 11 Issue 5, 2020. P.183-198. doi: 10.14569/IJACSA.2020.0110527
Lyudmyla Kirichenko, Tamara Radivilova, and Vitalii Bulakh. Machine Learning in Classification Time Series with Fractal Properties. Data, Vol.4, issue 1, 5, pp.1-13, 2019. doi:10.3390/data4010005
Yousef Ibrahim Daradkeh, Lyudmyla Kirichenko and Tamara Radivilova. Development of QoS Methods in the Information Networks with Fractal Traffic. Intl. Journal of Electronics and Telecommunications, 2018, Vol. 64, No. 1, pp. 27-32.

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Publikacje w materiałach konferencyjnych

Pichugina, O., Kirichenko, L., Radivilova, T Binary classification: Ensemble Methods Utilizing Decision Theory Tools CEUR Workshop Proceedings , 2022, 3348, pp. 19–33.
Kirichenko, L., Radivilova, T., Pichugina, O., Chala, L., Khandak, D. Trend Detection in Short Time Series Using Discrete Wavelet Transform , CEUR Workshop Proceedings , 2022, 3347, pp. 159–168.
L. Kirichenko, K. Pavlenko and D. Khatsko, "Wavelet-Based Estimation of Hurst Exponent Using Neural Network," 2022 IEEE 17th International Conference on Computer Sciences and Information Technologies (CSIT), Lviv, Ukraine, 2022, pp. 40-43, doi: 10.1109/CSIT56902.2022.10000906.
Kirichenko, Lyudmyla, Oksana Pichugina, Hlib Zinchenko. Clustering Time Series of Complex Dynamics by Features. International Conference "Information Technology and Interactions" (2021).
T. Radivilova, K. Lyudmyla, O. Lemeshko, D. Ageyev, M. Tawalbeh and A. Ilkov, "Analysis of Approaches of Monitoring, Intrusion Detection and Identification of Network Attacks," 2020 IEEE International Conference on Problems of Infocommunications. Science and Technology (PIC S&T), Kharkiv, Ukraine, 2020, pp. 819-822, doi: 10.1109/PICST51311.2020.9467973.
Kirichenko, L., Radivilova, T., Stepanenko, J. Applying recurrence plots to classify time series CEUR Workshop Proceedings, 2021, 2870, pp. 1770–1780
T. Radivilova, L. Kirichenko, O. Lemeshko, D. Ageyev, O. Mulesa and A. Ilkov, "Analysis of Anomaly Detection and Identification Methods in 5G Traffic," 2021 11th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS), Cracow, Poland, 2021, pp. 1108-1113, doi: 10.1109/IDAACS53288.2021.9660920.
L. Kirichenko, T. Radivilova, V. Bulakh, P. Zinchenko and A. Saif Alghawli. Two Approaches to Machine Learning Classification of Time Series Based on Recurrence Plots. 2020 IEEE Third International Conference on Data Stream Mining & Processing (DSMP), Lviv, Ukraine, 2020, pp. 84-89, doi: 10.1109/DSMP47368.2020.9204021.
Lyudmyla Kirichenko, Vitalii Bulakh, Tamara Radivilova. Machine learning classification of multifractional Brownian motion realizations. Proceedings of The Third International Workshop on Computer Modeling and Intelligent Systems (CMIS-2020). Zaporizhzhia, Ukraine, April 27-May 1, 2020. P.980-989. http://ceur-ws.org/Vol-2608/
T. Radivilova, L. Kirichenko and B. Vitalii. Comparative analysis of machine learning classification of time series with fractal properties. 2019 IEEE 8th International Conference on Advanced Optoelectronics and Lasers (CAOL), Sozopol, Bulgaria, 2019, pp. 557-560. doi: 10.1109/CAOL46282.2019.9019416
Lyudmyla Kirichenko, Petro Zinchenko, Tamara Radivilova, Maksym Tavalbeh. Machine Learning Detection of DDoS Attacks Based on Visualization of Recurrence Plots. In: Proceedings of the International Workshop on Conflict Management in Global Information Networks (CMiGIN 2019), Kyiv, 2019, pp.23-34.
T. Radivilova, L. Kirichenko, D. Ageyev, M. Tawalbeh, V. Bulakh and P. Zinchenko. Intrusion Detection Based on Machine Learning Using Fractal Properties of Traffic Realizations. 2019 IEEE International Conference on Advanced Trends in Information Theory (ATIT), Kyiv, Ukraine, 2019, pp. 218-221. doi: 10.1109/ATIT49449.2019.9030452
T. Radivilova, L. Kirichenko, D. Ageiev and V. Bulakh. Classification Methods of Machine Learning to Detect DDoS Attacks. 2019 10th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS), Metz, France, 2019, pp. 207-210. doi: 10.1109/IDAACS.2019.8924406
L. Kirichenko, T. Radivilova and V. Bulakh. Classification of Fractal Time Series Using Recurrence Plots. 2018 International Scientific-Practical Conference Problems of Infocommunications. Science and Technology (PIC S&T), Kharkiv, Ukraine, 2018, pp. 719-724. doi: 10.1109/INFOCOMMST.2018.8632010
V. Bulakh, L. Kirichenko and T. Radivilova. Time Series Classification Based on Fractal Properties. 2018 IEEE Second International Conference on Data Stream Mining & Processing (DSMP), Lviv, Ukraine, 2018, pp. 198-201. doi: 10.1109/DSMP.2018.8478532
Tamara Radivilova, Lyudmyla Kirichenko, Vitalii Bulakh. Classification of Multifractal Time Series by Decision Tree Methods. 14th International Conference ICTERI 2018 ICT in Education, Research, and Industrial Applications, 2018, p.1-4.

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