Parameter Estimation in Ordinary Differential Equations Modeling via Particle Swarm Optimization
Joint Authors
Akman, Devin
Akman, Olcay
Schaefer, Elsa
Source
Journal of Applied Mathematics
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-09-02
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Abstract EN
Researchers using ordinary differential equations to model phenomena face two main challenges among others: implementing the appropriate model and optimizing the parameters of the selected model.
The latter often proves difficult or computationally expensive.
Here, we implement Particle Swarm Optimization, which draws inspiration from the optimizing behavior of insect swarms in nature, as it is a simple and efficient method for fitting models to data.
We demonstrate its efficacy by showing that it outstrips evolutionary computing methods previously used to analyze an epidemic model.
American Psychological Association (APA)
Akman, Devin& Akman, Olcay& Schaefer, Elsa. 2018. Parameter Estimation in Ordinary Differential Equations Modeling via Particle Swarm Optimization. Journal of Applied Mathematics،Vol. 2018, no. 2018, pp.1-9.
https://search.emarefa.net/detail/BIM-1176087
Modern Language Association (MLA)
Akman, Devin…[et al.]. Parameter Estimation in Ordinary Differential Equations Modeling via Particle Swarm Optimization. Journal of Applied Mathematics No. 2018 (2018), pp.1-9.
https://search.emarefa.net/detail/BIM-1176087
American Medical Association (AMA)
Akman, Devin& Akman, Olcay& Schaefer, Elsa. Parameter Estimation in Ordinary Differential Equations Modeling via Particle Swarm Optimization. Journal of Applied Mathematics. 2018. Vol. 2018, no. 2018, pp.1-9.
https://search.emarefa.net/detail/BIM-1176087
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1176087