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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 |