Auflistung Факультет систем управління літальних апаратів (№ 3) nach Autor "Chumachenko, D."
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Assessing the impact of the Russian war in Ukraine on covid-19 transmission in Spain: a machine learning-based study
Chumachenko, D.; Dudkina, T.; Chumachenko, T. (ХАІ, 2023)The paper describes the results of an experimental study assessing the impact of the Russian full-scale war in Ukraine on COVID-19 dynamics in Spain. The developed model showed good performance to use it in public health ... -
Barriers of COVID-19 vaccination in ukraine during the war: the simulation study using arima model
Chumachenko, D.; Chumachenko, T.; Kirinovych, N.; Meniailov, I.; Muradyan, O.; Salun, O. (ХАІ, 2022)The purpose of the study is to develop a model of vaccination against COVID-19 in Ukraine and to study the impact of war on this process. The research is multidisciplinary and includes a sociological study of the attitude ... -
Comparative analysis of the machine learning models determining COVID-19 patient risk levels
Bazilevych, K.; Kyrylenko, O.; Parfenyuk, Y.; Krivtsov, S.; Meniailov, I.; Kuznietcova, V.; Chumachenko, D. (ХАІ, 2023)The COVID-19 pandemic has posed unprecedented challenges to global healthcare systems, emphasizing the need for predictive tools for resource allocation and patient care. This study delves into the potential of machine ... -
Comparative study of linear regression and sir models of covid-19 propagation in Ukraine before vaccination
Mohammadi, A.; Meniailov, I.; Bazilevych, K.; Yakovlev, S.; Chumachenko, D. (ХАІ, 2021)The study aims to develop machine learning and compartment models of COVID-19 epidemic process and to investigate experimental results of simulation. The object of research is COVID-19 epidemic process and its dynamics in ... -
Ensemble machine learning approaches for fake news classification
Padalko, H.; Chomko, V.; Yakovlev, S.; Chumachenko, D. (ХАІ, 2023)This study develops an ensemble machine learning model for fake news classification. The research is targeted at spreading fake news. The research subjects are machine learning methods for misinformation classification. -
Impact of war on COVID-19 pandemic in Ukraine: the simulation study
Chumachenko, D.; Pyrohov, P.; Meniailov, I.; Chumachenko, T. (ХАІ, 2022)This article describes experimental studies of implementing the COVID-19 epidemic pro-cess model in Ukraine based on the polynomial regression method. The constructed model was sufficiently ac-curate in deciding on ... -
Intelligent agent-based technologies for network worms simulation
Kamaeva, K.; Chumachenko, D. (Планета-прінт, 2019)As part of this study, a multi-agent model of network worm propagation has been developed using the example of the Code Red worm, which helps eliminate the shortcomings of deterministic analytical models. -
On COVID-19 epidemic process simulation: three regression approaches investigations
Chumachenko, D.; Meniailov, I.; Bazilevych, K.; Chub, O. (ХАІ, 2022)This paper describes experimental research on implementing three regression models of the COVID-19 epidemic process. These are models of linear regression, Ridge regression, and Lasso regression. COVID-19 daily new cases ... -
Predictive model of COVID-19 epidemic process based on neural network
Krivtsov, S.; Meniailov, I.; Bazilevych, K.; Chumachenko, D. (ХАІ, 2022)The purpose of the research is to build a model of the epidemic process of COVID-19 to predict its dynamics based on neural networks. The object of research is the epidemic process of infectious diseases using the example ... -
Simulation and forecasting of the influenza epidemic process using seasonal autoregressive integrated moving average model
Chumachenko, D.; Meniailov, I.; Hrimov, A.; Lopatka, V.; Moroz, O.; Tolstoluzka, O. (ХАІ, 2021)The study aims to develop a seasonal autoregressive integrated moving average (SARIMA) model for influenza epidemic process simulation and to investigate the experimental results of the simulation. The work is targeted at ...