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A new version of L1-Predictor-Corrector method to solve multiple delay-type fractional order systems with the example of a neural network model

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URI: http://hdl.handle.net/10498/35320

DOI: 10.1142/S0218348X23400431

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Author/s
Kumar, Pushpendra; Ertuk, V. S.; Murillo Arcila, MarinaAuthority UCA; Venkatesan, Govindaraj
Date
2023
Department
Matemáticas
Source
Fractals, 31(4) (2023), 2340043
Abstract
In this paper, we derive a new version of L1-Predictor–Corrector (L1-PC) method by using some previously given methods (L1-PC for single delay, PC for non-delay, and decomposition algorithm) to solve multiple delay-type fractional differential equations. The Caputo fractional derivative with singular type kernel is used to establish the results. Some important remarks related to the delay term estimation and error analysis are mentioned. In order to check the accuracy and correctness of our method, we solve a neural network system with two delay parameters. A number of graphs are given to justify the role of delays as well as the accuracy of the algorithm. The given method is fully novel and reliable to solve multiple delay type fractional order systems in Caputo sense.
Subjects
Neural Networks; Delay-Type Mathematical Model; Caputo Fractional Derivative; L1-Predictor–Corrector Method; Graphical Simulations
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