ИДЕНТИФИКАЦИЯ ПАРАМЕТРОВ ЭПИДЕМИЙ В ХОДЕ НЕЧЁТКОЙ ОПТИМИЗАЦИИ

Abstract

Target. Obtain an analytical form of an approximate solution for a system of firstorder nonlinear differential equations that describes the dynamics of the epidemic in the SI model of two cohorts: healthy – infected. Methodology. The solution is sought in the form of a logistic curve using one of three forms: normal distribution Ф, lognormal distribution L and risk function Risk. Results. During fuzzy optimization, the parameters of logistic curves are identified both during the solution of a system of differential equations with fixed parameters, and when constructing a predictive model based on the presented short section of historical data. Epidemic statistics are best interpreted by a possibilistic process, in the cross section of which there is a fuzzy number of a general form. Conclusion. The solution for the SI model is well approximated by logistic curves of type Ф. In a more complex case, both curves of type Ф and profile curves of Risk, determined on the basis of four parameters, are involved in the approximation.