parameter identification

INVERSE PROBLEM CHALLENGES OF MULTI-PULSE WAVE PROPAGATION IN HETEROGENEOUS MEDIA USING PHYSICS-INFORMED NEURAL NETWORKS

Developed an approach for studying inverse problems in multi-pulse wave propagation through non-uniform media, where overlapping signals make the recovery of coupled velocity profiles fundamentally ambiguous. Investigated an extension of Physics‑Informed Convolutional Neural Networks (PICNNs) to dual‑pulse scenarios to explain why ambiguity arises when two components propagate simultaneously in a heterogeneous medium.

The diffusion scattering parameters identification for a modified model of viral infection in the conditions of logistic dynamics of immunological cells

Based on the modification of the infectious disease model, taking into account diffusion disturbances and logistic dynamics of immunological cells, separate approaches to the diffusion scattering parameters identification for different types of functional dependence of diffusion coefficients and given redefinition conditions are proposed.  A special step-by-step procedure for numerically asymptotic approximation of the solution to the corresponding singularly perturbed model problem with a delay has been improved.  The results of computer experiments on identifying the