Parameter Estimation in the SIR Model Using Collocation Method

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27120%2F25%3A10259574" target="_blank" >RIV/61989100:27120/25:10259574 - isvavai.cz</a>

Výsledek na webu

<a href="https://rpsonline.com.sg/proceedings/esrel-sra-e2025/html/ESREL-SRA-E2025-P6771.html" target="_blank" >https://rpsonline.com.sg/proceedings/esrel-sra-e2025/html/ESREL-SRA-E2025-P6771.html</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.3850/978-981-94-3281-3_esrel-sra-e2025-p6771-cd" target="_blank" >10.3850/978-981-94-3281-3_esrel-sra-e2025-p6771-cd</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Parameter Estimation in the SIR Model Using Collocation Method

Popis výsledku v původním jazyce

In this paper, we present a methodology for estimating the parameters of a system of ordinary differential equations (ODEs) for the SIR model, a critical tool for understanding the dynamics of infectious diseases. The SIR model is essential for predicting outbreak patterns and informing public health interventions, playing a pivotal role in safety analysis. The parameters of the model are estimated from measured data while simultaneously solving the corresponding system of ODEs numerically. Our approach is based on the collocation method, where the solution is expressed as a linear combination of B-spline basis functions and fitted to the data through regression. The square Euclidean measure is used for both regression fitting and minimizing the ODE error. This problem is formulated as a multicriteria optimization task, balancing errors in the model fit and the numerical solution of the ODE system. The entire methodology is implemented in the MATLAB environment. We present numerical results and demonstrate the effectiveness of the approach for parameter estimation in epidemiological models using artificial benchmark datasets.

Název v anglickém jazyce

Parameter Estimation in the SIR Model Using Collocation Method

Popis výsledku anglicky

In this paper, we present a methodology for estimating the parameters of a system of ordinary differential equations (ODEs) for the SIR model, a critical tool for understanding the dynamics of infectious diseases. The SIR model is essential for predicting outbreak patterns and informing public health interventions, playing a pivotal role in safety analysis. The parameters of the model are estimated from measured data while simultaneously solving the corresponding system of ODEs numerically. Our approach is based on the collocation method, where the solution is expressed as a linear combination of B-spline basis functions and fitted to the data through regression. The square Euclidean measure is used for both regression fitting and minimizing the ODE error. This problem is formulated as a multicriteria optimization task, balancing errors in the model fit and the numerical solution of the ODE system. The entire methodology is implemented in the MATLAB environment. We present numerical results and demonstrate the effectiveness of the approach for parameter estimation in epidemiological models using artificial benchmark datasets.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

10102 - Applied mathematics

Projekt

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2025

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Proceedings of the 35th European Safety and Reliability Conference (ESREL 2025) and the 33rd Society for Risk Analysis Europe Conference (SRA-E 2025) : 15th June - 19th June 2025, University of Stavanger, Norway

ISBN

978-981-9432-81-3

ISSN

—

e-ISSN

—

Počet stran výsledku

8

Strana od-do

3274-3281

Název nakladatele

Research Publishing

Místo vydání

Singapur

Místo konání akce

Stavanger

Datum konání akce

15. 6. 2025

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

—