Loading [MathJax]/extensions/MathMenu.js
Optimized ANFIS-based Control Design Using Genetic Algorithm to Obtain the Vaccination and Isolation Rates for the COVID-19 | IEEE Conference Publication | IEEE Xplore

Optimized ANFIS-based Control Design Using Genetic Algorithm to Obtain the Vaccination and Isolation Rates for the COVID-19


Abstract:

In this work, an Adaptive-Network-based Fuzzy Inference System (ANFIS) control is designed and optimized with the Genetic Algorithm (GA) to control the COVID-19 described...Show More

Abstract:

In this work, an Adaptive-Network-based Fuzzy Inference System (ANFIS) control is designed and optimized with the Genetic Algorithm (GA) to control the COVID-19 described by the SEIAR (Susceptible - Exposed - Infected - Asymptomatic - Recovered) epidemic model. This work aims to reduce the number of infected and susceptible people by isolation and vaccination, respectively. In this regard, the ANFIS-based controller is designed. The GA is employed to generate an optimal data set by minimizing the appropriate objective function to train the ANFIS algorithm. The obtained results are evaluated via simulation in MATLAB® software to show the capability of the controller in overcoming the outbreak.
Date of Conference: 18-20 May 2021
Date Added to IEEE Xplore: 04 October 2021
ISBN Information:

ISSN Information:

Conference Location: Tehran, Iran, Islamic Republic of

Contact IEEE to Subscribe

References

References is not available for this document.