Neuro-evolution computing for nonlinear multi-singular system of third order Emden–Fowler equation

Zulqurnain Sabir, Muhammad Asif Zahoor Raja, Chaudry Masood Khalique and Canan Unlu

Mathematics and Computers in Simulation (MATCOM), 2021, vol. 185, issue C, 799-812

Abstract: In this paper, a neuro-evolution based numerical computing approach is presented for the solution of nonlinear third order multi-singular Emden–Fowler system of differential equations (MS-EF-SDEs) by manipulating the proficiency of continuous mapping through exploitation of feed-forward artificial neural networks (ANN). The weights or decision variables of these networks are optimized with genetic algorithms (GAs) and sequential quadratic programming (SQP), i.e., ANN-GA-SQP. An error based figure of merit is introduced using the differential model of MS EF-SDE along with corresponding boundary conditions. The objective/cost function is optimized by integrating capability of global and local search with GA and SQP, respectively. The competency of the designed ANN-GA-SQP approach in terms of significance, efficiency and consistency is perceived by solving MS-EF-SDEs. Moreover, statistical based investigations are implemented to validate the correctness of ANN-GA-SQP.

Keywords: System of Emden–Fowler equations; Multi-singular systems; Artificial neural network; Numerical computing; Genetic algorithms; Sequential quadratic programming; Integrated intelligent computing (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:matcom:v:185:y:2021:i:c:p:799-812

DOI: 10.1016/j.matcom.2021.02.004

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