Refet PolatBurhan PektasPektas, BurhanPolat, Refet2025-10-062025251944452519-444510.62476/amma.1024092-s2.0-105013097438https://www.scopus.com/inward/record.uri?eid=2-s2.0-105013097438&doi=10.62476%2Famma.102409&partnerID=40&md5=2c34dec5bdd5dde7faae1eeb7d29f39ehttps://gcris.yasar.edu.tr/handle/123456789/7982https://doi.org/10.62476/amma.102409In this paper the solution of the fractional partial differential-difference Toda Lattice Equation by Artificial Neural Networks is examined. According to the method we approximate the unknown values u<inf>n</inf> = u(. t<inf>n</inf>) of the desired function by the artificial neural networks. As an application we demonstrate the capabilities of this method for identification of various values of order of fractional derivative α. Thereafter the artificial neural networks algorithm is used in order to identify the unknown values u<inf>n</inf>. Comparing the results with the finite difference solution the algorithm can identify the function u(x t) better than the other method. © 2025 Elsevier B.V. All rights reserved.Englishinfo:eu-repo/semantics/openAccessA Source Identification, The Artificial Neural Network, The Wave EquationA Source IdentificationThe Wave EquationThe Artificial Neural NetworkArticle