@article{Bekesiene_Nakonechnyi_Kapustian_Shevchuk_Loseva_2023, title={Dynamics analysis and forecast of number of individuals with stress syndrome under uncertainties}, url={https://bphm.knu.ua/index.php/bphm/article/view/415}, DOI={10.17721/1812-5409.2023/2.35}, abstractNote={<p><em>In this work, we propose a population dynamics model of the spread of stressful processes in several groups with different characteristics. Such a model is described by a system of nonlinear differential equations. Also, this model provides for the possibility of studying external influences, that is, the effectiveness of actions aimed at increasing the psychological stability of the population. The main objective of the study was to propose algorithms for finding guaranteed predictive estimates of the dynamics of such models. Two scenarios of this challenge are considered: for the case when there are available accurate data on the number of persons under stressful influence in each of the groups during a specific time interval; and for a similar case, but when there is observational data on the dynamics of such individuals. In both cases, we apply the methodology of finding guaranteed predictive estimations of the dynamics within these models. As an example, we consider the special case of the equation of population dynamics without external influence for one group of persons.</em></p> <p><em><strong>Pages of the article in the issue</strong></em>: 195 - 199</p> <p><strong><em>Language of the article</em></strong>: English</p>}, number={2}, journal={Bulletin of Taras Shevchenko National University of Kyiv. Physical and Mathematical Sciences}, author={Bekesiene, S. and Nakonechnyi, O. and Kapustian, O. and Shevchuk, I. and Loseva, M.}, year={2023}, month={Dec.}, pages={195–199} }