Guirao, Juan L. G.Baleanu, DumitruSabir, ZulqurnainRaja, Muhammad Asif ZahoorBaleanu, DumitruMatematik2024-03-052024-03-052022Guirao, Juan L. G.;...et.al. (2022). "Design of neuro-swarming computational solver for the fractional Bagley–Torvik mathematical model", European Physical Journal Plus, Vol.137, No.2.2190-5444https://doi.org/10.1140/epjp/s13360-022-02421-3Raja, Muhammad Asif Zahoor/0000-0001-9953-822X; Guirao, Juan L.G./0000-0003-2788-809X; Sabir, Zulqurnain/0000-0001-7466-6233This study is to introduce a novel design and implementation of a neuro-swarming computational numerical procedure for numerical treatment of the fractional Bagley-Torvik mathematical model (FBTMM). The optimization procedures based on the global search with particle swarm optimization (PSO) and local search via active-set approach (ASA), while Mayer wavelet kernel-based activation function used in neural network (MWNNs) modeling, i.e., MWNN-PSOASA, to solve the FBTMM. The efficiency of the proposed stochastic solver MWNN-GAASA is utilized to solve three different variants based on the fractional order of the FBTMM. For the meticulousness of the stochastic solver MWNN-PSOASA, the obtained and exact solutions are compared for each variant of the FBTMM with reasonable accuracy. For the reliability of the stochastic solver MWNN-PSOASA, the statistical investigations are provided based on the stability, robustness, accuracy and convergence metrics.eninfo:eu-repo/semantics/openAccessArticle137210.1140/epjp/s13360-022-02421-32-s2.0-85125311915WOS:00075784160000135223352Q2Q2