TY - JOUR 
A1 - García Guirao, Juan Luis
AU - Sabir, Zulqurnain
AU - Zahoor Raja, Muhammad Asif
AU - Baleanu, Dumitru
T1 - Design of neuro-swarming computational solver for the fractional Bagley–Torvik mathematical model
Y1 - 2022
SN - 2190-5444
UR - http://hdl.handle.net/10317/12229
AB - This 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.
KW - Matemática Aplicada
KW - 12 Matemáticas
LA - eng
PB - SPRINGER
ER -