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A NEW FORM OF L1-PREDICTOR–CORRECTOR SCHEME TO SOLVE MULTIPLE DELAY-TYPE FRACTIONAL ORDER SYSTEMS WITH THE EXAMPLE OF A NEURAL NETWORK MODEL.

Authors :
KUMAR, PUSHPENDRA
ERTURK, VEDAT SUAT
MURILLO-ARCILA, MARINA
GOVINDARAJ, V.
Source :
Fractals; 2023, Vol. 31 Issue 4, p1-13, 13p
Publication Year :
2023

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. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
0218348X
Volume :
31
Issue :
4
Database :
Complementary Index
Journal :
Fractals
Publication Type :
Academic Journal
Accession number :
164820575
Full Text :
https://doi.org/10.1142/S0218348X23400431