Neural network methods to solve the Lane–Emden type equations arising in thermodynamic studies of the spherical gas cloud model

Neural network methods to solve the Lane–Emden type equations arising in thermodynamic studies of the spherical gas cloud model

In the present study, stochastic numerical computing approach is developed by applying artificial neural networks (ANNs) to compute the solution of Lane–Emden type boundary value problems arising in thermodynamic studies of the spherical gas cloud model. ANNs are used in an unsupervised manner to co...

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Main Authors: Ahmad, Iftikhar, Zahoor Raja, Muhammad Asif, Bilal, Muhammad, Ashraf, Farooq
Format: Article
Language:English
Published: Springer London 2017
Subjects:
T Technology (General)
Online Access:http://umpir.ump.edu.my/id/eprint/24135/
http://umpir.ump.edu.my/id/eprint/24135/
http://umpir.ump.edu.my/id/eprint/24135/
http://umpir.ump.edu.my/id/eprint/24135/1/Neural%20network%20methods%20to%20solve%20the%20Lane%E2%80%93Emden%20type%20equations%20arising%20in%20thermodynamic%20studies%20of%20the%20spherical%20gas%20cloud%20model.pdf
id ump-24135
recordtype eprints
spelling ump-241352019-03-14T08:48:31Z http://umpir.ump.edu.my/id/eprint/24135/ Neural network methods to solve the Lane–Emden type equations arising in thermodynamic studies of the spherical gas cloud model Ahmad, Iftikhar Zahoor Raja, Muhammad Asif Bilal, Muhammad Ashraf, Farooq T Technology (General) In the present study, stochastic numerical computing approach is developed by applying artificial neural networks (ANNs) to compute the solution of Lane–Emden type boundary value problems arising in thermodynamic studies of the spherical gas cloud model. ANNs are used in an unsupervised manner to construct the energy function of the system model. Strength of efficient local optimization procedures based on active-set (AS), interior-point (IP) and sequential quadratic programming (SQP) algorithms is used to optimize the energy functions. The performance of all three design methodologies ANN-AS, ANN-IP and ANN-SQP is evaluated on different nonlinear singular systems. The effectiveness of the proposed schemes in terms of accuracy and convergence is established from the results of statistical indicators. Springer London 2017-12 Article PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/24135/1/Neural%20network%20methods%20to%20solve%20the%20Lane%E2%80%93Emden%20type%20equations%20arising%20in%20thermodynamic%20studies%20of%20the%20spherical%20gas%20cloud%20model.pdf Ahmad, Iftikhar and Zahoor Raja, Muhammad Asif and Bilal, Muhammad and Ashraf, Farooq (2017) Neural network methods to solve the Lane–Emden type equations arising in thermodynamic studies of the spherical gas cloud model. Neural Computing and Applications, 28. pp. 929-944. ISSN 0941-0643 https://doi.org/10.1007/s00521-016-2400-y https://doi.org/10.1007/s00521-016-2400-y
repository_type Digital Repository
institution_category Local University
institution Universiti Malaysia Pahang
building UMP Institutional Repository
collection Online Access
language English
topic T Technology (General)
spellingShingle T Technology (General)
Ahmad, Iftikhar
Zahoor Raja, Muhammad Asif
Bilal, Muhammad
Ashraf, Farooq
Neural network methods to solve the Lane–Emden type equations arising in thermodynamic studies of the spherical gas cloud model
description In the present study, stochastic numerical computing approach is developed by applying artificial neural networks (ANNs) to compute the solution of Lane–Emden type boundary value problems arising in thermodynamic studies of the spherical gas cloud model. ANNs are used in an unsupervised manner to construct the energy function of the system model. Strength of efficient local optimization procedures based on active-set (AS), interior-point (IP) and sequential quadratic programming (SQP) algorithms is used to optimize the energy functions. The performance of all three design methodologies ANN-AS, ANN-IP and ANN-SQP is evaluated on different nonlinear singular systems. The effectiveness of the proposed schemes in terms of accuracy and convergence is established from the results of statistical indicators.
format Article
author Ahmad, Iftikhar
Zahoor Raja, Muhammad Asif
Bilal, Muhammad
Ashraf, Farooq
author_facet Ahmad, Iftikhar
Zahoor Raja, Muhammad Asif
Bilal, Muhammad
Ashraf, Farooq
author_sort Ahmad, Iftikhar
title Neural network methods to solve the Lane–Emden type equations arising in thermodynamic studies of the spherical gas cloud model
title_short Neural network methods to solve the Lane–Emden type equations arising in thermodynamic studies of the spherical gas cloud model
title_full Neural network methods to solve the Lane–Emden type equations arising in thermodynamic studies of the spherical gas cloud model
title_fullStr Neural network methods to solve the Lane–Emden type equations arising in thermodynamic studies of the spherical gas cloud model
title_full_unstemmed Neural network methods to solve the Lane–Emden type equations arising in thermodynamic studies of the spherical gas cloud model
title_sort neural network methods to solve the lane–emden type equations arising in thermodynamic studies of the spherical gas cloud model
publisher Springer London
publishDate 2017
url http://umpir.ump.edu.my/id/eprint/24135/
http://umpir.ump.edu.my/id/eprint/24135/
http://umpir.ump.edu.my/id/eprint/24135/
http://umpir.ump.edu.my/id/eprint/24135/1/Neural%20network%20methods%20to%20solve%20the%20Lane%E2%80%93Emden%20type%20equations%20arising%20in%20thermodynamic%20studies%20of%20the%20spherical%20gas%20cloud%20model.pdf
first_indexed 2023-09-18T22:36:22Z
last_indexed 2023-09-18T22:36:22Z
_version_ 1777416623113633792

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