Standard

Sensitivity analysis and practical identifiability of the mathematical model for partial differential equations. / Krivorotko, O.; Andornaya, D.

в: Journal of Physics: Conference Series, Том 2092, № 1, 012012, 20.12.2021.

Результаты исследований: Научные публикации в периодических изданиях › статья по материалам конференции › Рецензирование

Harvard

Krivorotko, O & Andornaya, D 2021, 'Sensitivity analysis and practical identifiability of the mathematical model for partial differential equations', Journal of Physics: Conference Series, Том. 2092, № 1, 012012. https://doi.org/10.1088/1742-6596/2092/1/012012

APA

Krivorotko, O., & Andornaya, D. (2021). Sensitivity analysis and practical identifiability of the mathematical model for partial differential equations. Journal of Physics: Conference Series, 2092(1), [012012]. https://doi.org/10.1088/1742-6596/2092/1/012012

Vancouver

Krivorotko O, Andornaya D. Sensitivity analysis and practical identifiability of the mathematical model for partial differential equations. Journal of Physics: Conference Series. 2021 дек. 20;2092(1):012012. doi: 10.1088/1742-6596/2092/1/012012

Author

Krivorotko, O. ; Andornaya, D. / Sensitivity analysis and practical identifiability of the mathematical model for partial differential equations. в: Journal of Physics: Conference Series. 2021 ; Том 2092, № 1.

BibTeX

@article{f3e90d5affc646cf89ac19d978b8758a,
title = "Sensitivity analysis and practical identifiability of the mathematical model for partial differential equations",
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.",
author = "O. Krivorotko and D. Andornaya",
note = "Funding Information: The work is supported by Mathematical Center in Akademgorodok, the agreement with Ministry of Science and High Education of the Russian Federation number 075-15-2019-1675. Publisher Copyright: {\textcopyright} 2021 Institute of Physics Publishing. All rights reserved.; 11th International Scientific Conference and Young Scientist School on Theory and Computational Methods for Inverse and Ill-posed Problems ; Conference date: 26-08-2019 Through 04-09-2019",
year = "2021",
month = dec,
day = "20",
doi = "10.1088/1742-6596/2092/1/012012",
language = "English",
volume = "2092",
journal = "Journal of Physics: Conference Series",
issn = "1742-6588",
publisher = "IOP Publishing Ltd.",
number = "1",

}

RIS

TY - JOUR

T1 - Sensitivity analysis and practical identifiability of the mathematical model for partial differential equations

AU - Krivorotko, O.

AU - Andornaya, D.

N1 - Funding Information: The work is supported by Mathematical Center in Akademgorodok, the agreement with Ministry of Science and High Education of the Russian Federation number 075-15-2019-1675. Publisher Copyright: © 2021 Institute of Physics Publishing. All rights reserved.

PY - 2021/12/20

Y1 - 2021/12/20

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=85123982510&partnerID=8YFLogxK

U2 - 10.1088/1742-6596/2092/1/012012

DO - 10.1088/1742-6596/2092/1/012012

M3 - Conference article

AN - SCOPUS:85123982510

VL - 2092

JO - Journal of Physics: Conference Series

JF - Journal of Physics: Conference Series

SN - 1742-6588

IS - 1

M1 - 012012

T2 - 11th International Scientific Conference and Young Scientist School on Theory and Computational Methods for Inverse and Ill-posed Problems

Y2 - 26 August 2019 through 4 September 2019

ER -

ID: 35454517