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Applications Of Gudermannian Neural Network For Solving The Sitr Fractal System

Author

Listed:
  • ZULQURNAIN SABIR

    (Department of Mathematics and Statistics, Hazara University, Mansehra, Pakistan)

  • MUHAMMAD UMAR

    (Department of Mathematics and Statistics, Hazara University, Mansehra, Pakistan)

  • MUHAMMAD ASIF ZAHOOR RAJA

    (��Future Technology Research Center, National Yunlin University of Science and Technology, 123 University Road, Section 3, Douliou, Yunlin 64002, Taiwan, R.O.C.)

  • DUMITRU BALEANU

    (��Department of Mathematics, Cankaya University, Ankara, Turkey§Institute of Space Science, Magurele-Bucharest, Romania)

Abstract

This study is related to explore the Gudermannian neural network (GNN) for solving a nonlinear SITR COVID-19 fractal system by using the optimization efficiencies of a genetic algorithm (GA), a global search technique and sequential quadratic programming (SQP) and a quick local search scheme, i.e. GNN-GA-SQP. The nonlinear SITR COVID-19 fractal system is dependent on four collections: “susceptible†, “infected†, “treatment†and “recovered†. For the optimization procedures through the GNN-GA-SQP, a merit function is constructed using the nonlinear SITR COVID-19 fractal system and its corresponding initial conditions. The description of each collection of the nonlinear SITR COVID-19 fractal system is provided along with comprehensive detail. The comparison of the achieved numerical result performances of each collection of the nonlinear SITR COVID-19 fractal system is performed with the Adams results to verify the exactness of the designed computational GNN-GA-SQP. The statistical processes based on different operators are presented for 30 independent trials using 5 neurons to authenticate the consistency of the designed computational GNN-GA-SQP. Moreover, the graphs of absolute error (AE), performance indices, and convergence measures along with the boxplots and histograms are also plotted to check the stability, exactness and reliability of the designed computational GNN-GA-SQP.

Suggested Citation

  • Zulqurnain Sabir & Muhammad Umar & Muhammad Asif Zahoor Raja & Dumitru Baleanu, 2021. "Applications Of Gudermannian Neural Network For Solving The Sitr Fractal System," FRACTALS (fractals), World Scientific Publishing Co. Pte. Ltd., vol. 29(08), pages 1-20, December.
    • Handle: RePEc:wsi:fracta:v:29:y:2021:i:08:n:s0218348x21502509
    DOI: 10.1142/S0218348X21502509
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    Cited by:

    1. Sabir, Zulqurnain & Said, Salem Ben & Baleanu, Dumitru, 2022. "Swarming optimization to analyze the fractional derivatives and perturbation factors for the novel singular model," Chaos, Solitons & Fractals, Elsevier, vol. 164(C).

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