Paper Info
Title
Design Of Stochastic Numerical Solver For The Solution Of Singular Three-Point Second-Order Boundary Value Problems
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.
Year
DOI
Venue
2021
10.1007/s00521-020-05143-8
NEURAL COMPUTING & APPLICATIONS
Keywords
DocType
Volume
Singular systems, Genetic algorithms, Hybrid approach, Artificial neural networks, Interior point algorithm
Journal
33
Issue
ISSN
Citations 
7
0941-0643
1
PageRank 
References 
Authors
0.36
0
4
Name
Order
Citations
PageRank
Zulqurnain Sabir1135.71
Dumitru Baleanu233878.57
Muhammad Shoaib3126388.37
Muhammad Asif Zahoor Raja455145.88