Title
Nature-inspired computing approach for solving non-linear singular Emden–Fowler problem arising in electromagnetic theory
Abstract
In this research, the well-known non-linear Lane–Emden–Fowler LEF equations are approximated by developing a nature-inspired stochastic computational intelligence algorithm. A trial solution of the model is formulated as an artificial feed-forward neural network model containing unknown adjustable parameters. From the LEF equation and its initial conditions, an energy function is constructed that is used in the algorithm for the optimisation of the networks in an unsupervised way. The proposed scheme is tested successfully by applying it on various test cases of initial value problems of LEF equations. The reliability and effectiveness of the scheme are validated through comprehensive statistical analysis. The obtained numerical results are in a good agreement with their corresponding exact solutions, which confirms the enhancement made by the proposed approach.
Year
DOI
Venue
2015
10.1080/09540091.2015.1092499
Connection Science
Keywords
Field
DocType
computational intelligence,neural networks,particle swarm optimisation,pattern search,interior-point method,hybrid computing,singular initial value problems
Nonlinear system,Computational intelligence,Computer science,Test case,Initial value problem,Artificial intelligence,Artificial neural network,Interior point method,Electromagnetic theory,Pattern search,Machine learning
Journal
Volume
Issue
ISSN
27
4
0954-0091
Citations 
PageRank 
References 
22
0.63
21
Authors
5
Name
Order
Citations
PageRank
Junaid Ali Khan11869.15
Muhammad Asif Zahoor Raja255145.88
M.M. Rashidi314022.72
Muhammed I. Syam49610.54
Abdul-Majid Wazwaz52711673.89