NUMERICAL INVESTIGATIONS OF A FRACTIONAL NONLINEAR DENGUE MODEL USING ARTIFICIAL NEURAL NETWORKS

Zulqurnain Sabir (), Muhammad Asif Zahoor Raja (), Shumaila Javeed and Yolanda Guerrero-Sã Nchez
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Zulqurnain Sabir: 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.
Shumaila Javeed: ��Department of Mathematics, COMSATS University Islamabad, Islamabad Campus, Park Road, Chak Shahzad Islamabad 45550, Pakistan§Near East University, Mathematics Research Center, Department of Mathematics, Near East Boulevard, PC 99138, Nicosia/Mersin 10, Turkey
Yolanda Guerrero-Sã Nchez: �Department of Anatomy and Psychobiology, University of Murcia, Murcia 30100, Spain

FRACTALS (fractals), 2022, vol. 30, issue 10, 1-12

Abstract: The aim of this study is to perform the numerical investigations of a fractional nonlinear dengue model using artificial neuron networks (ANNs) along with the Levenberg–Marquardt backpropagation (LMB), i.e. ANNs. The fractional nonlinear dengue model is divided into five classes. The stochastic-based ANNs-LMB scheme is pragmatic on three variants of authentication, training and testing. The data magnitudes for three different variations based on the fractional nonlinear dengue model are selected as 80% for training, 10% for both testing and validation. The numerical procedures of the fractional nonlinear dengue model will be performed through ANNs-LMB and comparative investigations using the reference values that are calculated on the basis of Adams–Bashforth–Moulton scheme. The solution of the fractional nonlinear dengue model is obtained through the ANNs-LMB to reduce the mean square error (MSE). To authenticate the capability and efficiency of the proposed ANNs-LMB, the obtained numerical measures of correlation, MSE results, regression and error histograms (EHs) are provided.

Keywords: Fractional Dengue Model; Artificial Neural Networks; Nonlinear; Adams–Bashforth–Moulton Scheme; Levenberg–Marquardt Backpropagation (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1142/S0218348X22402411

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