Staff Members - Benha University
FRACTIONAL MEYER NEURAL NETWORK PROCEDURES OPTIMIZED BY THE GENETIC ALGORITHM TO SOLVE THE BAGLEY-TORVIK MODEL
, Journal of Applied Analysis & Computation • 2023
Publication Information
Authors
Zulqurnain Sabir, Muhammad Asif Zahoor Raja, R. Sadat, Khaled. S. Ahmed, Mohamed R. Ali, and Wael Al-Kouz
Keywords
Fractional Meyer neural network; Bagley–Torvik model; Genetic algorithm;
Statistical analysis; Interior-point algorithm
Journal
, Journal of Applied Analysis & Computation
Publisher
Not Available
Volume
Not Available
Issue
Not Available
Pages
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publication.type
International
Paper Link
Not Available
Supplementary Materials
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Abstract
: The current investigations are related to indicate a competent numerical fractional
Meyer neural network (FMNN) procedure using the optimization of genetic algorithm and interiorpoint algorithm (GAIPA), i.e., FMNN-GAIPA for solving the Bagley–Torvik model (BTM). A
merit function based on the differential BTM form, and its corresponding initial conditions is
constructed and then optimized with the FMNN-GAIPA. Three different BTM cases will be solved
through the FMNN-GAIPA and the correctness of the proposed FMNN-GAIPA is observed by
using the comparison for each case of the BTM with the exact solutions. The statistical
investigations based on the appropriate large independent trials recognized the constancy of the
FMNN-GAIPA in terms of robustness, convergence, and stability trials. In addition, the
annotations over the statistical measures validate the values of FMNN-GAIPA
Meyer neural network (FMNN) procedure using the optimization of genetic algorithm and interiorpoint algorithm (GAIPA), i.e., FMNN-GAIPA for solving the Bagley–Torvik model (BTM). A
merit function based on the differential BTM form, and its corresponding initial conditions is
constructed and then optimized with the FMNN-GAIPA. Three different BTM cases will be solved
through the FMNN-GAIPA and the correctness of the proposed FMNN-GAIPA is observed by
using the comparison for each case of the BTM with the exact solutions. The statistical
investigations based on the appropriate large independent trials recognized the constancy of the
FMNN-GAIPA in terms of robustness, convergence, and stability trials. In addition, the
annotations over the statistical measures validate the values of FMNN-GAIPA