APPLICATIONS OF GUDERMANNIAN NEURAL NETWORK FOR SOLVING THE SITR FRACTAL SYSTEM

Zulqurnain Sabir, Muhammad Umar (), Muhammad Asif Zahoor Raja () and Dumitru Baleanu
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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

FRACTALS (fractals), 2021, vol. 29, issue 08, 1-20

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.

Keywords: Gudermannian Function; SITR COVID-19 Fractal System; Nonlinear; Genetic Algorithm; Reference Solutions; Sequential Quadratic Programming (search for similar items in EconPapers)
Date: 2021
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DOI: 10.1142/S0218348X21502509

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