Abundant soliton solution for the time-fractional stochastic Gray-Scot model under the influence of noise and M-truncated derivative

Baber, M.Z., Ahmed, N., Yasin, M.W. et al. (4 more authors) (2024) Abundant soliton solution for the time-fractional stochastic Gray-Scot model under the influence of noise and M-truncated derivative. Discover Applied Sciences, 6 (3). 119. ISSN 3004-9261

Abstract

Metadata

Item Type: Article
Authors/Creators:
  • Baber, M.Z.
  • Ahmed, N.
  • Yasin, M.W.
  • Ali, S.M.
  • Ali, M.
  • Akgül, A.
  • Hassani, M.K.
Copyright, Publisher and Additional Information: © The Author(s) 2024. Open Access: This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
Keywords: Soliton solutions; M-truncated derivative; Stochastic Gray-Scot (TFSGS) model; New MEDA technique
Dates:
  • Submitted: 23 December 2023
  • Accepted: 27 February 2024
  • Published (online): 11 March 2024
  • Published: 11 March 2024
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Electronic and Electrical Engineering (Sheffield)
Depositing User: Symplectic Sheffield
Date Deposited: 20 Mar 2024 11:03
Last Modified: 20 Mar 2024 11:03
Status: Published
Publisher: Springer Science and Business Media LLC
Refereed: Yes
Identification Number: https://doi.org/10.1007/s42452-024-05759-8

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