1. //
  2. Start
  3. //
  4. Publications
  5. Estimation of Parameters in the SIR Mode...
  6. Output formats
  7. //

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

Standard

Estimation of Parameters in the SIR Model Using a Particle Swarm Optimization Algorithm. / Marquardt, Niklas; Hendriok, Leo; Haus, Benedikt et al.
Advances in Data-Driven Computing and Intelligent Systems - Selected Papers from ADCIS 2023. ed. / Swagatam Das; Snehanshu Saha; Carlos A. Coello Coello; Hemant Rathore; Jagdish Chand Bansal. Springer Science and Business Media Deutschland, 2024. p. 157-167 (Lecture Notes in Networks and Systems; Vol. 890).

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

Harvard

Marquardt, N, Hendriok, L, Haus, B & Mercorelli, P 2024, Estimation of Parameters in the SIR Model Using a Particle Swarm Optimization Algorithm. in S Das, S Saha, CAC Coello, H Rathore & JC Bansal (eds), Advances in Data-Driven Computing and Intelligent Systems - Selected Papers from ADCIS 2023. Lecture Notes in Networks and Systems, vol. 890, Springer Science and Business Media Deutschland, pp. 157-167, 2nd International Conference on Advances in Data-driven Computing and Intelligent Systems - ADCIS 2023, BITS Pilani, India, 21.09.23. https://doi.org/10.1007/978-981-99-9531-8_13

APA

Marquardt, N., Hendriok, L., Haus, B., & Mercorelli, P. (2024). Estimation of Parameters in the SIR Model Using a Particle Swarm Optimization Algorithm. In S. Das, S. Saha, C. A. C. Coello, H. Rathore, & J. C. Bansal (Eds.), Advances in Data-Driven Computing and Intelligent Systems - Selected Papers from ADCIS 2023 (pp. 157-167). (Lecture Notes in Networks and Systems; Vol. 890). Springer Science and Business Media Deutschland. https://doi.org/10.1007/978-981-99-9531-8_13

Vancouver

Marquardt N, Hendriok L, Haus B, Mercorelli P. Estimation of Parameters in the SIR Model Using a Particle Swarm Optimization Algorithm. In Das S, Saha S, Coello CAC, Rathore H, Bansal JC, editors, Advances in Data-Driven Computing and Intelligent Systems - Selected Papers from ADCIS 2023. Springer Science and Business Media Deutschland. 2024. p. 157-167. (Lecture Notes in Networks and Systems). doi: 10.1007/978-981-99-9531-8_13

Bibtex

@inbook{485e40066e36443285be65ecc75ec255,
title = "Estimation of Parameters in the SIR Model Using a Particle Swarm Optimization Algorithm",
abstract = "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.",
keywords = "Lotka-Volterra model, Parameter identification, Particle Swarm Optimization, Engineering",
author = "Niklas Marquardt and Leo Hendriok and Benedikt Haus and Paolo Mercorelli",
note = "Publisher Copyright: {\textcopyright} The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.; 2nd International Conference on Advances in Data-driven Computing and Intelligent Systems - ADCIS 2023, ADCIS 2023 ; Conference date: 21-09-2023 Through 23-09-2023",
year = "2024",
doi = "10.1007/978-981-99-9531-8_13",
language = "English",
isbn = "978-981-99-9530-1",
series = "Lecture Notes in Networks and Systems",
publisher = "Springer Science and Business Media Deutschland",
pages = "157--167",
editor = "Swagatam Das and Snehanshu Saha and Coello, {Carlos A. Coello} and Hemant Rathore and Bansal, {Jagdish Chand}",
booktitle = "Advances in Data-Driven Computing and Intelligent Systems - Selected Papers from ADCIS 2023",
address = "Germany",
url = "https://scrs.in/conference/adcis23",

}

RIS

TY - CHAP

T1 - Estimation of Parameters in the SIR Model Using a Particle Swarm Optimization Algorithm

AU - Marquardt, Niklas

AU - Hendriok, Leo

AU - Haus, Benedikt

AU - Mercorelli, Paolo

N1 - Conference code: 2

PY - 2024

Y1 - 2024

N2 - 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.

AB - 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.

KW - Lotka-Volterra model

KW - Parameter identification

KW - Particle Swarm Optimization

KW - Engineering

UR - http://www.scopus.com/inward/record.url?scp=85192136759&partnerID=8YFLogxK

U2 - 10.1007/978-981-99-9531-8_13

DO - 10.1007/978-981-99-9531-8_13

M3 - Article in conference proceedings

AN - SCOPUS:85192136759

SN - 978-981-99-9530-1

T3 - Lecture Notes in Networks and Systems

SP - 157

EP - 167

BT - Advances in Data-Driven Computing and Intelligent Systems - Selected Papers from ADCIS 2023

A2 - Das, Swagatam

A2 - Saha, Snehanshu

A2 - Coello, Carlos A. Coello

A2 - Rathore, Hemant

A2 - Bansal, Jagdish Chand

PB - Springer Science and Business Media Deutschland

T2 - 2nd International Conference on Advances in Data-driven Computing and Intelligent Systems - ADCIS 2023

Y2 - 21 September 2023 through 23 September 2023

ER -

Other publications by the same author(s)

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

Pimentel, G. O., Santos, M. F. D., Lima, J., Mercorelli, P. & Fernandes, F. M., 15.01.2025, In: Sensors. 25, 2, 27 p., 479.

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.

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

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

Die geometry influence on the texture and microstructure development during extrusion of AZ31 and ZK60 magnesium alloy chips

Hendriok, L., Nienaber, M., Kurz, G. & Ben Khalifa, N., 01.2025, In: Materials and Design. 249, 13 p., 113545.

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

Dynamic Performance Analysis and Fault Ride-Through Enhancement by a Modified Fault Current Protection Scheme of a Grid-Connected Doubly Fed Induction Generator

Talani, R. A., Kaloi, G. S., Ali, A., Bijarani, M. A., Abbas, G., Hatatah, M., Mercorelli, P. & Touti, E., 02.2025, In: Machines. 13, 2, 20 p., 110.

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

DOI

Recently viewed

Activities

  1. Detection of tactical patterns using semi-supervised graph neural networks
  2. From Task Interpretation to Task Performance: Sampling Procedures in Researching Learner Perceptions of Web-Supported Tasks
  3. Taking ICALL to task: Blending form-focus & task-based foreign language learning
  4. Masked Autoencoder Pretraining for Event Classification in Elite Soccer
  5. Institutional Proxy Representatives of Future Generations: A Comparative Analysis of Types and Design Features
  6. Domestication and/or Digital Divide – How to Overcome Binary Classifications in Analysing Everyday Internet Use and Diffusion
  7. SIAM Conference on Applications of Dynamical Systems - DS 2023
  8. How, when, and why do negotiators use reference points? A qualitative interview study with negotiation experts.
  9. A Dynamic Signal Analyzer. Analysis and Synthesis of Speech at the Biological Computer Laboratory
  10. Reconsidering performativity in alternativity: Forward an otative management science

Publications

  1. Median based algorithm as an entropy function for noise detectionin wavelet trees for data reconciliation
  2. Advanced Neural Classifier-Based Effective Human Assistance Robots Using Comparable Interactive Input Assessment Technique
  3. A Wavelet Based Algorithm without a Priori Knowledge of Noise Level for Gross Errors Detection
  4. Fostering Circularity: Building a Local Community and Implementing Circular Processes
  5. Calculation of Average Mutual Information (AMI) and false-nearest neighbors (FNN) for the estimation of embedding parameters of multidimensional time series in matlab
  6. Modeling and Performance Analysis of a Node in Fault Tolerant Wireless Sensor Networks
  7. Discourse Analyses in Chat-based CSCL with Learning Protocols
  8. Database Publishing Without Databases
  9. A Lightweight Simulation Model for Soft Robot's Locomotion and its Application to Trajectory Optimization
  10. Transformer with Tree-order Encoding for Neural Program Generation
  11. Closed-loop control of product geometry by using an artificial neural network in incremental sheet forming with active medium
  12. Preventive Emergency Detection Based on the Probabilistic Evaluation of Distributed, Embedded Sensor Networks
  13. A transfer operator based computational study of mixing processes in open flow systems
  14. Automatic enumeration of all connected subgraphs.
  15. Methodologies for Noise and Gross Error Detection using Univariate Signal-Based Approaches in Industrial Application
  16. Enabling Road Condition Monitoring with an on-board Vehicle Sensor Setup
  17. Efficient and accurate ℓ p-norm multiple kernel learning
  18. Neural network-based adaptive fault-tolerant control for strict-feedback nonlinear systems with input dead zone and saturation
  19. Different complex word problems require different combinations of cognitive skills
  20. Semantic Parsing for Knowledge Graph Question Answering with Large Language Models
  21. Control of the inverse pendulum based on sliding mode and model predictive control
  22. Clustering Hydrological Homogeneous Regions and Neural Network Based Index Flood Estimation for Ungauged Catchments
  23. Latent structure perceptron with feature induction for unrestricted coreference resolution
  24. Selecting and Adapting Methods for Analysis and Design in Value-Sensitive Digital Social Innovation Projects: Toward Design Principles
  25. Modeling Effective and Ineffective Knowledge Communication and Learning Discourses in CSCL with Hidden Markov Models
  26. Problem structuring for transitions
  27. Using Decision Trees and Reinforcement Learning for the Dynamic Adjustment of Composite Sequencing Rules in a Flexible Manufacturing System
  28. Spatial mislocalization as a consequence of sequential coding of stimuli
  29. DialogueMaps: Supporting interactive transdisciplinary dialogues with a web-based tool for multi-layer knowledge maps
  30. Real-time RDF extraction from unstructured data streams
  31. A Multivariate Method for Dynamic System Analysis
  32. On the Decoupling and Output Functional Controllability of Robotic Manipulation
  33. Analysis of long-term statistical data of cobalt flows in the EU
  34. Supporting the Development and Implementation of a Digitalization Strategy in SMEs through a Lightweight Architecture-based Method
  35. FFTSMC with Optimal Reference Trajectory Generated by MPC in Robust Robotino Motion Planning with Saturating Inputs