The paper is devoted to a numerical study of the uniqueness and stability of problems of determining the parameters of dynamical systems arising in pharmacokinetics, immunology, epidemiology, sociology, etc. by incomplete measurements of certain states of the system at fixed time. Significance of parameters difficult to measure is very high in many areas, as their definition will allow physicians and doctors to make an effective treatment plan and to select the optimal set of medicines. Due to the fact that the problems under consideration are ill-posed, it is necessary to investigate the degree of ill-posedness before its numerical solution. One of the most effective ways is to study the practical identifiability of systems of nonlinear ordinary differential equations that will allow us to establish a set of identifiable parameters for further numerical solution of inverse problems. The paper presents methods for investigating practical identifiability: the Monte Carlo method, the matrix correlation method, the confidence intervals method and the sensitivity based method. There is presented two mathematical models of the pharmacokinetics of the C-peptide and mathematical model of the spread of the COV ID − 19 epidemic. The identifiability investigation will allow us to construct a regularized unique solution of the inverse problem.

Original languageEnglish
Article number012014
JournalJournal of Physics: Conference Series
Issue number1
Publication statusPublished - 20 Dec 2021
Event11th International Scientific Conference and Young Scientist School on Theory and Computational Methods for Inverse and Ill-posed Problems - Novosibirsk, Russian Federation
Duration: 26 Aug 20194 Sep 2019




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