Parameters and order identification of fractional-order epidemiological systems by Lévy-PSO and its application for the spread of COVID-19

Bing Xie and Fudong Ge

Chaos, Solitons & Fractals, 2023, vol. 168, issue C

Abstract: To identify the knowledge about parameters and order is very important for the modeling of fractional-order epidemiological systems. In this paper, such an identification problem is formulated as a nonlinear optimization problem. For solving this, the Lévy-PSO algorithm, which is obtained by applying Lévy flight to generalize the classical particle swarm optimization (PSO), is used. More precisely, we first utilize Lévy-PSO to identify the constant parameters and the order of fractional-order SIR, SEIR systems with simulated data to show the effectiveness of our proposed identification strategy. Then, we continue employing Lévy-PSO to solve the parameter estimation problem of fractional-order SEAIR model under the real data of COVID-19 in Shanghai from 2/26/2022 to 4/27/2022. Numerical examples and associated comparisons with other existing methods allow us to achieve that our proposed identification strategy can generate a good performance with high accuracy and rapid convergence.

Keywords: Parameters identification; Order identification; Nonlinear optimization problem; Fractional-order epidemiological systems; Lévy-PSO (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (3)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:chsofr:v:168:y:2023:i:c:s0960077923000644

DOI: 10.1016/j.chaos.2023.113163

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