Результаты исследований: Научные публикации в периодических изданиях › статья › Рецензирование
Sensitivity Analysis and Practical Identifiability of Some Mathematical Models in Biology. / Krivorotko, O. I.; Andornaya, D. V.; Kabanikhin, S. I.
в: Journal of Applied and Industrial Mathematics, Том 14, № 1, 12, 20.03.2020, стр. 115-130.Результаты исследований: Научные публикации в периодических изданиях › статья › Рецензирование
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TY - JOUR
T1 - Sensitivity Analysis and Practical Identifiability of Some Mathematical Models in Biology
AU - Krivorotko, O. I.
AU - Andornaya, D. V.
AU - Kabanikhin, S. I.
N1 - Криворотько О.И., Андорная Д.В., Кабанихин С.И. Анализ чувствительности и практическая идентифицируемость математических моделей биологии // Сибирский журнал индустриальной математики. – 2020. – Т. 23. – № 1. – С. 107-125.
PY - 2020/3/20
Y1 - 2020/3/20
N2 - We study the identifiability of some mathematical models of spreading TB and HIV coinfections in a population and the dynamics of HIV-infection at the cellular level. Sensitivity analysis is carried out using the orthogonal method and the eigenvalue method which are based on studying the properties of the sensitivity matrix and show the effect of the model coefficient change on simulation results. Practical identifiability is investigated which determines the possibility of reconstructing coefficients from the noisy experimental data. The analysis is performed using the correlation matrix and Monte Carlo method, while taking into consideration the Gaussian noise in measurements. The results of numerical calculations are presented on whose basis we obtain the identifiable sets of parameters.
AB - We study the identifiability of some mathematical models of spreading TB and HIV coinfections in a population and the dynamics of HIV-infection at the cellular level. Sensitivity analysis is carried out using the orthogonal method and the eigenvalue method which are based on studying the properties of the sensitivity matrix and show the effect of the model coefficient change on simulation results. Practical identifiability is investigated which determines the possibility of reconstructing coefficients from the noisy experimental data. The analysis is performed using the correlation matrix and Monte Carlo method, while taking into consideration the Gaussian noise in measurements. The results of numerical calculations are presented on whose basis we obtain the identifiable sets of parameters.
KW - identifiability
KW - inverse problem
KW - method of correlation matrix
KW - Monte Carlo method
KW - ordinary differential equations
KW - sensitivity analysis
KW - sensitivity matrix
UR - http://www.scopus.com/inward/record.url?scp=85082390445&partnerID=8YFLogxK
UR - https://elibrary.ru/item.asp?id=43256965
U2 - 10.1134/S1990478920010123
DO - 10.1134/S1990478920010123
M3 - Article
AN - SCOPUS:85082390445
VL - 14
SP - 115
EP - 130
JO - Journal of Applied and Industrial Mathematics
JF - Journal of Applied and Industrial Mathematics
SN - 1990-4789
IS - 1
M1 - 12
ER -
ID: 23893011