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Estimation of Parameters in the SIR Model Using a Particle Swarm Optimization Algorithm

Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review

Authors

The paper deals with the estimation of parameters in the Susceptible-Infected-Removed (SIR) model of infectious disease transmission in populations using an algorithm based on a Particle Swarm Optimization (PSO) method. The used model in this contribution is based on the dynamics of predator and prey populations. A possible model is represented by the Lotka-Volterra model which is used in such kinds of competitive ecosystems. SIR models can be considered as a particular form of Lotka-Volterra models, in which susceptible and infected people represent the prey and predator. The main contribution of this investigation consists of showing how the model can reflect the real data using a low number of compartments in case the model parameters are estimated adaptively using an optimal procedure. A PSO method is used in a receding horizon window-like structure to estimate these parameters. The procedure is validated using real values of the COVID-19 pandemic in Germany, demonstrating a close matching.

Original languageEnglish
Title of host publicationAdvances in Data-Driven Computing and Intelligent Systems - Selected Papers from ADCIS 2023
EditorsSwagatam Das, Snehanshu Saha, Carlos A. Coello Coello, Hemant Rathore, Jagdish Chand Bansal
Number of pages11
PublisherSpringer Science and Business Media Deutschland
Publication date2024
Pages157-167
ISBN (print)978-981-99-9530-1
ISBN (electronic)978-981-99-9531-8
DOIs
Publication statusPublished - 2024
Event2nd International Conference on Advances in Data-driven Computing and Intelligent Systems - ADCIS 2023 - BITS Pilani, India
Duration: 21.09.2023 → 23.09.2023
Conference number: 2
https://scrs.in/conference/adcis23

Bibliographical note

Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

    Research areas

  • Lotka-Volterra model, Parameter identification, Particle Swarm Optimization
  • Engineering

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Research output: Contributions to collected editions/works › Contributions to collected editions/anthologies › Research › peer-review

An Over-Actuated Hexacopter Tilt-Rotor UAV Prototype for Agriculture of Precision: Modeling and Control

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Research output: Journal contributions › Journal articles › Research › peer-review

Automatic Tuning of Extended Kalman Filter in Synchronous Reluctance Motor Drives with a Master-Slave Configuration

Rigon, S., Haus, B., Mercorelli, P. & Zigliotto, M., 27.02.2025, In: IEEE Open Journal of Power Electronics. 6, p. 734-746 13 p.

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Business Analytics and Making Decision Based on Kalman Filter in Stock Prediction Case

Kurniawan, S. & Mercorelli, P., 27.05.2025, 5th Congress on Intelligent Systems, CIS 2024: Volume 1. Kumar, S., Mary Anita, E. A., Kim, J. H. & Nagar, A. (eds.). Springer Science and Business Media Deutschland, p. 309-320 12 p. (Lecture Notes in Networks and Systems; vol. 1275).

Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review

Control Allocation and Controller Tuning for an Over-Actuated Hexacopter Tilt-Rotor Applied for Precision Agriculture

Libório, L. O., Pimentel, G. O., Dos Santos, M. F., Fernandes, F. M., Lima, J., De Morais, M. H. F., Mercorelli, P. & Pereira, A. I., 2025, Proceedings of the 2025 26th International Carpathian Control Conference, ICCC 2025. Kacur, J., Skovranek, T., Laciak, M. & Mojzisova, A. (eds.). Institute of Electrical and Electronics Engineers Inc., (Proceedings of the 2025 26th International Carpathian Control Conference, ICCC 2025).

Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review

DOI

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