ISSN 0869-6632 (Print)
ISSN 2542-1905 (Online)


Population dynamics

SIRS-model with dynamic regulation of the population: Probabilistic cellular automata approach

Aim. Construction a model of infection spread in the form of a lattice of stochastic cellular automata which can demonstrate nontrivial oscillating regimes; investigation of its dynamics and comparison with the mean-field model. Method. Numerical simulation of the square lattice of cellular automata by the Monte Carlo approach, theoretical and numerical study of the structure of the phase space of its mean-field model. Results. A modified SIRS-model of epidemic propagation has been proposed in the form of a lattice of stochastic cellular automata.

Bifurcations in active predator – passive prey model

  Bifurcations were studied numerically in the system of partial differential equations, which is  a one variant of predator-prey models. The mathematical model takes into account spatial  distribution in habitat, active directed predator movements, birth and death process in prey  population. The analysis of possible population dynamics development was performed by two  qualitatively different discrete sampling techniques (Bubnov–Galerkin’s method and grid method).