Solution of the one-dimensional Bratu equation arising in the fuel ignition model using ANN optimised with PSO and SQP

In this paper, an efficient procedure based on the neural networks methodology is presented for the solution of the fuel ignition model in one dimension. The neural networks were optimised with the particle swarm optimisation algorithm hybridised with sequential quadratic programming. The accuracy a...

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Bibliographic Details
Published in:Connection science Vol. 26; no. 3; pp. 195 - 214
Main Author: Raja, Muhammad Asif Zahoor
Format: Journal Article
Language:English
Published: Abingdon Taylor & Francis 01.09.2014
Taylor & Francis Ltd
Subjects:
Accuracy
boundary value problems
Convergence
Monte Carlo simulation
Neural networks
Optimization algorithms
particle swarm optimisation
Quadratic programming
sequential quadratic programming
solid fuel ignition model
ISSN:0954-0091, 1360-0494
Online Access:Get full text
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Summary:In this paper, an efficient procedure based on the neural networks methodology is presented for the solution of the fuel ignition model in one dimension. The neural networks were optimised with the particle swarm optimisation algorithm hybridised with sequential quadratic programming. The accuracy and convergence of the scheme are analysed by Monte Carlo simulations and their statistical analyses for three test cases of the problem represented by Bratu-type equations. It was found that the hybrid approach converges in all cases, and can solve the problem with higher accuracy and reliability than most of the methodologies used so far to solve this problem.
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ISSN:0954-0091
1360-0494
DOI:10.1080/09540091.2014.907555