2021
DOI: 10.3390/math9222894
|View full text |Cite
|
Sign up to set email alerts
|

On Some Features of the Numerical Solving of Coefficient Inverse Problems for an Equation of the Reaction-Diffusion-Advection-Type with Data on the Position of a Reaction Front

Abstract: The work continues a series of articles devoted to the peculiarities of solving coefficient inverse problems for nonlinear singularly perturbed equations of the reaction-diffusion-advection-type with data on the position of the reaction front. In this paper, we place the emphasis on some problems of the numerical solving process. One of the approaches to solving inverse problems of the class under consideration is the use of methods of asymptotic analysis. These methods, under certain conditions, make it possi… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1

Citation Types

0
2
0

Year Published

2022
2022
2023
2023

Publication Types

Select...
6

Relationship

1
5

Authors

Journals

citations
Cited by 6 publications
(3 citation statements)
references
References 76 publications
0
2
0
Order By: Relevance
“…Despite the small amount of known data, we managed to make an assumption regarding the time of the mutations' accumulation to a number sufficient for the appearance of visible differences in individuals in the mouse population and found that the initial set of mice in the experiment described in [22] already consisted of at least two phenotypically different groups of mice. This result was possible thanks to the active development of methods for solving coefficient inverse problems for partial differential equations with data on curves inside the domain (see [34][35][36][37][38][39]).…”
Section: Discussionmentioning
confidence: 99%
“…Despite the small amount of known data, we managed to make an assumption regarding the time of the mutations' accumulation to a number sufficient for the appearance of visible differences in individuals in the mouse population and found that the initial set of mice in the experiment described in [22] already consisted of at least two phenotypically different groups of mice. This result was possible thanks to the active development of methods for solving coefficient inverse problems for partial differential equations with data on curves inside the domain (see [34][35][36][37][38][39]).…”
Section: Discussionmentioning
confidence: 99%
“…The second research area is the inverse problems involving second-order differential equations, which are also non-linear mathematical problems [18]. Still, compared to the classical differential equation solvers, they require a completely different handling, since the functions to be determined are the coefficients of the differential equation [19][20][21]. All these research activities are supported by a solid foundation in exact schemes, which, as effective and robust mathematical methods, provide new perspectives for basic research.…”
Section: Introductionmentioning
confidence: 99%
“…Fractional operators and corresponding differential and integral equations are often chosen because of the memory effects provided by their analytical properties [8][9][10][11][12][13][14][15]. However, when it comes to a mathematical problem, the solution is derived from a real model, the theoretical results of which are often not directly applicable to the given problem.…”
Section: Introductionmentioning
confidence: 99%