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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

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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

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dc.contributor.author Kumar, Pushpendra es_ES
dc.contributor.author Ertürk, Vedat Suat es_ES
dc.contributor.author Murillo-Arcila, Marina es_ES
dc.contributor.author Govindaraj V. es_ES
dc.date.accessioned 2023-10-23T18:01:15Z
dc.date.available 2023-10-23T18:01:15Z
dc.date.issued 2023-04 es_ES
dc.identifier.issn 0218-348X es_ES
dc.identifier.uri http://hdl.handle.net/10251/198608
dc.description.abstract [EN] 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. es_ES
dc.description.sponsorship M. Murillo-Arcila is supported by MCIN/AEI/10.13039/501100011033, Project PID2019-105011 GBI00 and by Generalitat Valenciana, Project PROMETEU/2021/070. es_ES
dc.language Inglés es_ES
dc.publisher World Scientific es_ES
dc.relation.ispartof Fractals es_ES
dc.rights Reconocimiento - No comercial - Sin obra derivada (by-nc-nd) es_ES
dc.subject Neural Networks es_ES
dc.subject Delay-Type Mathematical Model es_ES
dc.subject Caputo Fractional Derivative es_ES
dc.subject L1-Predictor-Corrector Method es_ES
dc.subject Graphical Simulations es_ES
dc.title A New Form Of L1-Predictor-Corrector Scheme To Solve Multiple Delay-Type Fractional Order Systems With The Example Of A Neural Network Model es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1142/S0218348X23400431 es_ES
dc.relation.projectID info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2019-105011GB-I00/ES/DINAMICA DE OPERADORES/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/GVA//PROMETEO%2F2021%2F070/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/AEI//PID2019-105011GB-I00//DINAMICA DE OPERADORES/ es_ES
dc.rights.accessRights Abierto es_ES
dc.description.bibliographicCitation Kumar, P.; Ertürk, VS.; Murillo-Arcila, M.; Govindaraj V. (2023). A New Form Of L1-Predictor-Corrector Scheme To Solve Multiple Delay-Type Fractional Order Systems With The Example Of A Neural Network Model. Fractals. 31(4):1-13. https://doi.org/10.1142/S0218348X23400431 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.1142/S0218348X23400431 es_ES
dc.description.upvformatpinicio 1 es_ES
dc.description.upvformatpfin 13 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 31 es_ES
dc.description.issue 4 es_ES
dc.relation.pasarela S\501640 es_ES
dc.contributor.funder Generalitat Valenciana es_ES
dc.contributor.funder Agencia Estatal de Investigación es_ES
upv.costeAPC 2600 es_ES


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