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Artificial neural networks to solve the singular model with Neumann–Robin, Dirichlet and Neumann boundary conditions

The aim of this work is to solve the case study singular model involving the Neumann–Robin, Dirichlet, and Neumann boundary conditions using a novel computing framework that is based on the artificial neural network (ANN), global search genetic algorithm (GA), and local search sequential quadratic p...

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Main Authors: Kashif Nisar, Zulqurnain Sabir, Muhammad Asif Zahoor Raja, Ag. Asri Ag. Ibrahim, Rodrigues, Joel J. P. C., Samy Refahy Mahmoud, Bhawani Shankar Chowdhry, Manoj Gupta
Format: Article
Language:English
English
Published: Multidisciplinary Digital Publishing Institute 2021
Subjects:
QA1-939 Mathematics
Online Access:https://eprints.ums.edu.my/id/eprint/32589/1/Artificial%20neural%20networks%20to%20solve%20the%20singular%20model%20with%20neumann%E2%80%93robin%2C%20dirichlet%20and%20neumann%20boundary%20conditions%20%20_ABSTRACT.pdf
https://eprints.ums.edu.my/id/eprint/32589/2/Artificial%20neural%20networks%20to%20solve%20the%20singular%20model%20with%20neumann%E2%80%93robin%2C%20dirichlet%20and%20neumann%20boundary%20conditions.pdf
https://eprints.ums.edu.my/id/eprint/32589/
https://www.mdpi.com/1424-8220/21/19/6498/htm
https://doi.org/10.3390/s21196498
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spelling my.ums.eprints.325892022-05-18T04:27:39Z https://eprints.ums.edu.my/id/eprint/32589/ Artificial neural networks to solve the singular model with Neumann–Robin, Dirichlet and Neumann boundary conditions Kashif Nisar Zulqurnain Sabir Muhammad Asif Zahoor Raja Ag. Asri Ag. Ibrahim Rodrigues, Joel J. P. C. Samy Refahy Mahmoud Bhawani Shankar Chowdhry Manoj Gupta QA1-939 Mathematics The aim of this work is to solve the case study singular model involving the Neumann–Robin, Dirichlet, and Neumann boundary conditions using a novel computing framework that is based on the artificial neural network (ANN), global search genetic algorithm (GA), and local search sequential quadratic programming method (SQPM), i.e., ANN-GA-SQPM. The inspiration to present this numerical framework comes through the objective of introducing a reliable structure that associates the operative ANNs features using the optimization procedures of soft computing to deal with such stimulating systems. Four different problems that are based on the singular equations involving Neumann–Robin, Dirichlet, and Neumann boundary conditions have been occupied to scrutinize the robustness, stability, and proficiency of the designed ANN-GA-SQPM. The proposed results through ANN-GA-SQPM have been compared with the exact results to check the efficiency of the scheme through the statistical performances for taking fifty independent trials. Moreover, the study of the neuron analysis based on three and 15 neurons is also performed to check the authenticity of the proposed ANN-GA-SQPM. Multidisciplinary Digital Publishing Institute 2021 Article PeerReviewed text en https://eprints.ums.edu.my/id/eprint/32589/1/Artificial%20neural%20networks%20to%20solve%20the%20singular%20model%20with%20neumann%E2%80%93robin%2C%20dirichlet%20and%20neumann%20boundary%20conditions%20%20_ABSTRACT.pdf text en https://eprints.ums.edu.my/id/eprint/32589/2/Artificial%20neural%20networks%20to%20solve%20the%20singular%20model%20with%20neumann%E2%80%93robin%2C%20dirichlet%20and%20neumann%20boundary%20conditions.pdf Kashif Nisar and Zulqurnain Sabir and Muhammad Asif Zahoor Raja and Ag. Asri Ag. Ibrahim and Rodrigues, Joel J. P. C. and Samy Refahy Mahmoud and Bhawani Shankar Chowdhry and Manoj Gupta (2021) Artificial neural networks to solve the singular model with Neumann–Robin, Dirichlet and Neumann boundary conditions. Sensors, 21 (6498). pp. 1-15. ISSN 1996-2022 https://www.mdpi.com/1424-8220/21/19/6498/htm https://doi.org/10.3390/s21196498
institution Universiti Malaysia Sabah
building UMS Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Sabah
content_source UMS Institutional Repository
url_provider http://eprints.ums.edu.my/
language English
English
topic QA1-939 Mathematics
spellingShingle QA1-939 Mathematics
Kashif Nisar
Zulqurnain Sabir
Muhammad Asif Zahoor Raja
Ag. Asri Ag. Ibrahim
Rodrigues, Joel J. P. C.
Samy Refahy Mahmoud
Bhawani Shankar Chowdhry
Manoj Gupta
Artificial neural networks to solve the singular model with Neumann–Robin, Dirichlet and Neumann boundary conditions
description The aim of this work is to solve the case study singular model involving the Neumann–Robin, Dirichlet, and Neumann boundary conditions using a novel computing framework that is based on the artificial neural network (ANN), global search genetic algorithm (GA), and local search sequential quadratic programming method (SQPM), i.e., ANN-GA-SQPM. The inspiration to present this numerical framework comes through the objective of introducing a reliable structure that associates the operative ANNs features using the optimization procedures of soft computing to deal with such stimulating systems. Four different problems that are based on the singular equations involving Neumann–Robin, Dirichlet, and Neumann boundary conditions have been occupied to scrutinize the robustness, stability, and proficiency of the designed ANN-GA-SQPM. The proposed results through ANN-GA-SQPM have been compared with the exact results to check the efficiency of the scheme through the statistical performances for taking fifty independent trials. Moreover, the study of the neuron analysis based on three and 15 neurons is also performed to check the authenticity of the proposed ANN-GA-SQPM.
format Article
author Kashif Nisar
Zulqurnain Sabir
Muhammad Asif Zahoor Raja
Ag. Asri Ag. Ibrahim
Rodrigues, Joel J. P. C.
Samy Refahy Mahmoud
Bhawani Shankar Chowdhry
Manoj Gupta
author_facet Kashif Nisar
Zulqurnain Sabir
Muhammad Asif Zahoor Raja
Ag. Asri Ag. Ibrahim
Rodrigues, Joel J. P. C.
Samy Refahy Mahmoud
Bhawani Shankar Chowdhry
Manoj Gupta
author_sort Kashif Nisar
title Artificial neural networks to solve the singular model with Neumann–Robin, Dirichlet and Neumann boundary conditions
title_short Artificial neural networks to solve the singular model with Neumann–Robin, Dirichlet and Neumann boundary conditions
title_full Artificial neural networks to solve the singular model with Neumann–Robin, Dirichlet and Neumann boundary conditions
title_fullStr Artificial neural networks to solve the singular model with Neumann–Robin, Dirichlet and Neumann boundary conditions
title_full_unstemmed Artificial neural networks to solve the singular model with Neumann–Robin, Dirichlet and Neumann boundary conditions
title_sort artificial neural networks to solve the singular model with neumann–robin, dirichlet and neumann boundary conditions
publisher Multidisciplinary Digital Publishing Institute
publishDate 2021
url https://eprints.ums.edu.my/id/eprint/32589/1/Artificial%20neural%20networks%20to%20solve%20the%20singular%20model%20with%20neumann%E2%80%93robin%2C%20dirichlet%20and%20neumann%20boundary%20conditions%20%20_ABSTRACT.pdf
https://eprints.ums.edu.my/id/eprint/32589/2/Artificial%20neural%20networks%20to%20solve%20the%20singular%20model%20with%20neumann%E2%80%93robin%2C%20dirichlet%20and%20neumann%20boundary%20conditions.pdf
https://eprints.ums.edu.my/id/eprint/32589/
https://www.mdpi.com/1424-8220/21/19/6498/htm
https://doi.org/10.3390/s21196498
_version_ 1760231046881738752
score 13.211869

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