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- W4283694728 abstract "This paper portrays the exploitation/exploration of artificial intelligence (AI) inspired computing to study the behavior of the multi-delay differential systems that revealed the impact of latent period and the dynamics of the a susceptible, vaccinated, exposed, infectious and recovered (SVEIR) epidemic model involving vaccination by means of the neural networks backpropagation with Levenberg–Marquardt scheme (NNs-BLMS). The reference solutions of the five classes ordinary differential equations (ODEs) model of SVEIR dynamics are calculated by applying the Adams method for variation in delay due to the time spent in preventing the infection and delay due to the duration of recovery immunity in the cured population. The designed NNs-BLMS used the created dataset arbitrarily for training, validation, as well as, testing samples to determine the estimated results of the nonlinear SVEIR epidemic model involving vaccination impact. The achieved accuracy of the designed NNs-BLMS is authenticated/proven by analyzing the fitness function based on mean square error (MSE), regression analysis, and error histogram for sundry scenarios of SVEIR epidemic system with the impact of vaccination." @default.
- W4283694728 created "2022-06-30" @default.
- W4283694728 creator A5048315421 @default.
- W4283694728 creator A5061378172 @default.
- W4283694728 creator A5064574696 @default.
- W4283694728 creator A5069175841 @default.
- W4283694728 creator A5074368763 @default.
- W4283694728 creator A5080585392 @default.
- W4283694728 date "2022-06-28" @default.
- W4283694728 modified "2023-10-17" @default.
- W4283694728 title "Intelligent networks knacks for numerical treatment of nonlinear multi-delays SVEIR epidemic systems with vaccination" @default.
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- W4283694728 doi "https://doi.org/10.1142/s0217979222501004" @default.