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Journal of Artificial Intelligence and Soft Computing Research

The Journal of Polish Neural Network Society, the University of Social Sciences in Lodz & Czestochowa University of Technology

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A Smart Amalgamation of Spectral Neural Algorithm for Nonlinear Lane-Emden Equations with Simulated Annealing

Najeeb Alam Khan / Amber Shaikh
Published Online: 2017-03-20 | DOI: https://doi.org/10.1515/jaiscr-2017-0015


The actual motivation of this paper is to develop a functional link between artificial neural network (ANN) with Legendre polynomials and simulated annealing termed as Legendre simulated annealing neural network (LSANN). To demonstrate the applicability, it is employed to study the nonlinear Lane-Emden singular initial value problem that governs the polytropic and isothermal gas spheres. In LSANN, minimization of error is performed by simulated annealing method while Legendre polynomials are used in hidden layer to control the singularity problem. Many illustrative examples of Lane-Emden type are discussed and results are compared with the formerly used algorithms. As well as with accuracy of results and tranquil implementation it provides the numerical solution over the entire finite domain.

Keywords: Lane-Emden equations; simulated annealing; legendre polynomials; neural network


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About the article

Received: 2016-01-01

Accepted: 2016-07-04

Published Online: 2017-03-20

Published in Print: 2017-07-01

Citation Information: Journal of Artificial Intelligence and Soft Computing Research, Volume 7, Issue 3, Pages 215–224, ISSN (Online) 2083-2567, DOI: https://doi.org/10.1515/jaiscr-2017-0015.

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© 2017 Academy of Management (SWSPiZ), Lodz. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License. BY-NC-ND 3.0

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