Abstract

A sensitivity-based identifiability analysis of mathematical model for partial differential equations is carried out using an orthogonal method and an eigenvalue method. These methods are used to study the properties of the sensitivity matrix and the effects of changes in the model coefficients on the simulation results. Practical identifiability is investigated to determine whether the coefficients can be reconstructed with noisy experimental data. The analysis is performed using correlation matrix method with allowance for Gaussian noise in the measurements. The results of numerical calculations to obtain identifiable sets of parameters for the mathematical model arising in social networks are presented and discussed.

Original languageEnglish
Article number012012
JournalJournal of Physics: Conference Series
Volume2092
Issue number1
DOIs
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

OECD FOS+WOS

  • 1.03 PHYSICAL SCIENCES AND ASTRONOMY

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