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Numerical Computational Heuristic Through Morlet Wavelet Neural Network for Solving the Dynamics of Nonlinear SITR COVID-19

查看全文 作　　者：Zulqurnain [1]Sabir;Abeer [2]S.Alnahdi;Mdi Begum [2]Jeelani;Mohamed [2,3]A.Abdelkawy;Muhammad Asif Zahoor [4]Raja;Dumitru [5,6]Baleanu;Muhammad Mubashar [7]Hussain 高影响力作者 机构地区：[1]Department of Mathematics,Hazara University,Mansehra,Pakistan;[2]Department of Mathematics and Statistics,Faculty of Science,Imam Mohammad Ibn Saud Islamic University(IMSIU),Riyadh,Saudi Arabia;[3]Department of Mathematics,Faculty of Science,Beni-Suef University,Beni-Suef,Egypt;[4]Future Technology Research Center,National Yunlin University of Science and Technology,Yunlin,Taiwan;[5]Department of Mathematics,Cankaya University,Ankara,Turkey;[6]Institute of Space Sciences,Magurele-Bucharest,Romania;[7]Department of Mathematics,University of Punjab,Jhelum Campus,Jhelum,Pakistan高影响力机构 出　　处：《Computer Modeling in Engineering & Sciences》索引2022年第5期,共23页高影响力期刊 基　　金：The authors extend their appreciation to the Deanship of Scientific Research at Imam Mohammad Ibn Saud Islamic University for funding this work through Research Group No.RG-21-09-12. 摘　　要：The present investigations are associated with designing Morlet wavelet neural network(MWNN)for solving a class of susceptible,infected,treatment and recovered(SITR)fractal systems of COVID-19 propagation and control.The structure of an error function is accessible using the SITR differential form and its initial conditions.The optimization is performed using the MWNN together with the global as well as local search heuristics of genetic algorithm(GA)and active-set algorithm(ASA),i.e.,MWNN-GA-ASA.The detail of each class of the SITR nonlinear COVID-19 system is also discussed.The obtained outcomes of the SITR system are compared with the Runge-Kutta results to check the perfection of the designed method.The statistical analysis is performed using different measures for 30 independent runs as well as 15 variables to authenticate the consistency of the proposed method.The plots of the absolute error,convergence analysis,histogram,performancemeasures,and boxplots are also provided to find the exactness,dependability and stability of the MWNN-GA-ASA. 关 键 词：Nonlinear SITR model morlet function artificial neural networks RUNGE-KUTTA TREATMENT genetic algorithm TREATMENT active-set
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