An Investigation Through Stochastic Procedures for Solving the Fractional Order Computer Virus Propagation Mathematical Model with Kill Signals

Sabir, Zulqarnain and Raja, Muhammad Asif Zahoor and Mumtaz, Nadia and Fathurrochman, Irwan and Ali, Mohamed R (2022) An Investigation Through Stochastic Procedures for Solving the Fractional Order Computer Virus Propagation Mathematical Model with Kill Signals. Neural Processing Letters - Springer.

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Official URL: https://link.springer.com/article/10.1007/s11063-0...

Abstract

In this study, the numerical investigations through the stochastic procedures for solving a class of fractional order (FO) computer virus propagation (CVP) mathematical model with kill signals (KS), i.e., CVP-KS is presented. The KS gets alert about those viruses, which can be infected through the computer system to decrease the virus propagation danger. The mathematical model of the CVP-KS is based on the SEIR-KS model. The focus of these investigations is to present the numerical solutions of the FO-SEIR-KS model using thesense of Levenberg–Marquardt backpropagation scheme (LMBS) together with the neural networks (NNs), i.e., LMBS-NNs. The use of the one dynamic of the other makes the model nonlinear. Three different FO values have been used to check the performances of the designed scheme for this FO-SEIR-KS nonlinear mathematical model. The statics used in this study is 80%, 10% and 10% for training, testing and certification for solving the FOSEIR-KS nonlinear mathematical model. The numerical simulations are performed through the stochastic LMBS-NNs scheme for solving the FO-SEIR-KS nonlinear mathematical model. The obtained results will be compared with the design of database reference solutions based on the Adams–Bashforth–Moulton. In order to accomplish the validity, capability, consistency, competence and accuracy of the LMBS-NNs, the numerical results using the error histograms, regression, mean square error, state transitions and correlation have been provided.

Item Type: Article
Creators:
CreatorsEmail
Sabir, ZulqarnainUNSPECIFIED
Raja, Muhammad Asif ZahoorUNSPECIFIED
Mumtaz, NadiaUNSPECIFIED
Fathurrochman, Irwanirwan@iaincurup.ac.id
Ali, Mohamed RUNSPECIFIED
Subjects: L Education > L Education (General)
Q Science > Q Science (General)
Q Science > QA Mathematics
Divisions: Fakultas Tarbiyah > Manajemen Pendidikan Islam
Depositing User: Mrs Maisona Maisona
Date Deposited: 11 Aug 2022 08:15
Last Modified: 20 Sep 2022 02:16
URI: http://repository.iaincurup.ac.id/id/eprint/1015

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