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...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English English |
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Multidisciplinary Digital Publishing Institute
2021
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| 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 |
| _version_ | 1825714719798853632 |
|---|---|
| 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 |
| collection | UMS |
| 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. |
| first_indexed | 2024-03-06T03:15:59Z |
| format | Article |
| id | ums.eprints-32589 |
| institution | Universiti Malaysia Sabah |
| language | English English |
| last_indexed | 2024-03-06T03:15:59Z |
| publishDate | 2021 |
| publisher | Multidisciplinary Digital Publishing Institute |
| record_format | dspace |
| spelling | 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 https://doi.org/10.3390/s21196498 |
| 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 |
| title | 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_short | 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 |
| topic | QA1-939 Mathematics |
| 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 |
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