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Neural Computing and Applications

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02-07-2020 | Original Article

Design of stochastic numerical solver for the solution of singular three-point second-order boundary value problems

Authors: Zulqurnain Sabir, Dumitru Baleanu, Muhammad Shoaib, Muhammad Asif Zahoor Raja

Published in: Neural Computing and Applications | Issue 7/2021

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Abstract

In this paper, a novel meta-heuristic computing solver is presented for solving the singular three-point second-order boundary value problems using artificial neural networks (ANNs) optimized by the combined strength of global and local search ability of genetic algorithms (GAs) and interior point algorithm (IPA), i.e., ANN–GA–IPA. The inspiration for presenting this numerical work comes from the intention of introducing a consistent framework that combines the effective features of neural networks optimized with the contexts of soft computing to handle with such challenging systems. Three numerical variants of singular second-order system have been taken to examine the proficiency, robustness, and stability of the designed approach. The comparison of the proposed results of ANN–GA–IPA from available exact solutions shows the good agreement with 5 to 7 decimal places of the accuracy which established worth of the methodology through performance analyses on a single and multiple executions.

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Title: Design of stochastic numerical solver for the solution of singular three-point second-order boundary value problems
Authors: Zulqurnain Sabir
Dumitru Baleanu
Muhammad Shoaib
Muhammad Asif Zahoor Raja
Publication date: 02-07-2020
Publisher: Springer London
Published in: Neural Computing and Applications / Issue 7/2021
Print ISSN: 0941-0643
Electronic ISSN: 1433-3058
DOI: https://doi.org/10.1007/s00521-020-05143-8

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