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Optimization of Coronavirus Pandemic Model Through artificial Intelligence

Computers, Materials & Continua 2023年第3期74卷 6807-6822页

作者： Manal M.Alqarni Arooj Nasir Dumitru Baleanu Ali Raza Tahir Nawaz Cheema Nauman Ahmed Muhammad Rafiq Umbreen Fatima Emad E.Mahmoud Department of Mathematics College of SciencesKing Khalid UniversityAbha61413Saudi Arabia Baqai Medical University Karachi75340Pakistan Shalamar Medical and Dental College Lahore54000Pakistan Department of Mathematics Cankaya UniversityBalgatAnkara06530Turkey Department of Medical Research China Medical UniversityTaichung40402TaiwanChina Institute of Space Sciences Magurele-Bucharest077125Romania Department of Mathematics Govt.Maulana Zafar Ali Khan Graduate College WazirabadPunjab Higher Education Department(PHED)Lahore54000Pakistan Department of Mathematics University of GujratGujrat52200Pakistan Department of Mathematics and Statistics The University of LahoreLahore54590Pakistan Department of Mathematics Faculty of Science and TechnologyUniversity of Central PunjabLahore54000Pakistan Department of Computer Science University of LahoreLahore54590Pakistan Department of Mathematics and Statistics College of ScienceTaif UniversityP.O.Box11099Taif21944Saudi Arabia

artificial intelligence is demonstrated by machines,unlike the natural intelligence displayed by animals,including *** intelligence research has been defined as the field of study of intelligent agents,which refers to any system that perceives its environment and takes actions that maximize its chance of achieving its *** techniques of intelligent computing solve many applications of mathematical *** researchworkwas designed via a particularmethod of artificial neural networks to solve the mathematical model of *** representation of the mathematical model is made via systems of nonlinear ordinary differential *** differential equations are established by collecting the susceptible,the exposed,the symptomatic,super spreaders,infection with asymptomatic,hospitalized,recovery,and fatality *** generation of the coronavirus model’s dataset is exploited by the strength of the explicit Runge Kutta method for different countries like India,Pakistan,Italy,and many *** generated dataset is approximately used for training,validation,and testing processes for each cyclic update in Bayesian Regularization Backpropagation for the numerical treatment of the dynamics of the desired *** performance and effectiveness of the designed methodology are checked through mean squared error,error histograms,numerical solutions,absolute error,and regression analysis.

关键词： Coronavirus model artificial techniques analysis

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