Evolutionary integrated heuristic with gudermannian neural networks for second kind of lane– emden nonlinear singular models
In this work, a new heuristic computing design is presented with an artificial intelligence approach to exploit the models with feed-forward (FF) Gudermannian neural networks (GNN) accomplished with global search capability of genetic algorithms (GA) combined with local convergence aptitude of activ...
| Main Authors: | , , , , , , , , |
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| Format: | Article |
| Language: | English English |
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MDPI
2021
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| Online Access: | https://eprints.ums.edu.my/id/eprint/30009/1/Evolutionary%20integrated%20heuristic%20with%20gudermannian%20neural%20networks%20for%20second%20kind%20of%20lane%E2%80%93emden%20nonlinear%20singular%20models-Abstract.pdf https://eprints.ums.edu.my/id/eprint/30009/2/Evolutionary%20integrated%20heuristic%20with%20gudermannian%20neural%20networks%20for%20second%20kind%20of%20lane%E2%80%93emden%20nonlinear%20singular%20models.pdf |
| _version_ | 1825714280714993664 |
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| author | Kashif Nisar Zulqurnain Sabir Muhammad Asif Zahoor Raja Ag. Asri Ag. Ibrahim Joel J. P. C. Rodrigues Adnan Shahid Khan Manoj Gupta Aldawoud Kamal Danda B. Rawat |
| author_facet | Kashif Nisar Zulqurnain Sabir Muhammad Asif Zahoor Raja Ag. Asri Ag. Ibrahim Joel J. P. C. Rodrigues Adnan Shahid Khan Manoj Gupta Aldawoud Kamal Danda B. Rawat |
| author_sort | Kashif Nisar |
| collection | UMS |
| description | In this work, a new heuristic computing design is presented with an artificial intelligence approach to exploit the models with feed-forward (FF) Gudermannian neural networks (GNN) accomplished with global search capability of genetic algorithms (GA) combined with local convergence aptitude of active-set method (ASM), i.e., FF-GNN-GAASM to solve the second kind of Lane–Emden nonlinear singular models (LE-NSM). The proposed method based on the computing intelligent Gudermannian kernel is incorporated with the hidden layer configuration of FF-GNN models of differential operatives of the LE-NSM, which are arbitrarily associated with presenting an error-based objective function that is used to optimize by the hybrid heuristics of GAASM. Three LE-NSM-based examples are numerically solved to authenticate the effectiveness, accurateness, and efficiency of the suggested FF-GNN-GAASM. The reliability of the scheme via statistical valuations is verified in order to authenticate the stability, accuracy, and convergence |
| first_indexed | 2024-03-06T03:09:28Z |
| format | Article |
| id | ums.eprints-30009 |
| institution | Universiti Malaysia Sabah |
| language | English English |
| last_indexed | 2024-03-06T03:09:28Z |
| publishDate | 2021 |
| publisher | MDPI |
| record_format | dspace |
| spelling | ums.eprints-300092021-07-22T00:26:46Z https://eprints.ums.edu.my/id/eprint/30009/ Evolutionary integrated heuristic with gudermannian neural networks for second kind of lane– emden nonlinear singular models Kashif Nisar Zulqurnain Sabir Muhammad Asif Zahoor Raja Ag. Asri Ag. Ibrahim Joel J. P. C. Rodrigues Adnan Shahid Khan Manoj Gupta Aldawoud Kamal Danda B. Rawat QA Mathematics T Technology (General) In this work, a new heuristic computing design is presented with an artificial intelligence approach to exploit the models with feed-forward (FF) Gudermannian neural networks (GNN) accomplished with global search capability of genetic algorithms (GA) combined with local convergence aptitude of active-set method (ASM), i.e., FF-GNN-GAASM to solve the second kind of Lane–Emden nonlinear singular models (LE-NSM). The proposed method based on the computing intelligent Gudermannian kernel is incorporated with the hidden layer configuration of FF-GNN models of differential operatives of the LE-NSM, which are arbitrarily associated with presenting an error-based objective function that is used to optimize by the hybrid heuristics of GAASM. Three LE-NSM-based examples are numerically solved to authenticate the effectiveness, accurateness, and efficiency of the suggested FF-GNN-GAASM. The reliability of the scheme via statistical valuations is verified in order to authenticate the stability, accuracy, and convergence MDPI 2021-05-21 Article PeerReviewed text en https://eprints.ums.edu.my/id/eprint/30009/1/Evolutionary%20integrated%20heuristic%20with%20gudermannian%20neural%20networks%20for%20second%20kind%20of%20lane%E2%80%93emden%20nonlinear%20singular%20models-Abstract.pdf text en https://eprints.ums.edu.my/id/eprint/30009/2/Evolutionary%20integrated%20heuristic%20with%20gudermannian%20neural%20networks%20for%20second%20kind%20of%20lane%E2%80%93emden%20nonlinear%20singular%20models.pdf Kashif Nisar and Zulqurnain Sabir and Muhammad Asif Zahoor Raja and Ag. Asri Ag. Ibrahim and Joel J. P. C. Rodrigues and Adnan Shahid Khan and Manoj Gupta and Aldawoud Kamal and Danda B. Rawat (2021) Evolutionary integrated heuristic with gudermannian neural networks for second kind of lane– emden nonlinear singular models. Applied Sciences, 11. pp. 1-16. ISSN 2076-3417 https://www.mdpi.com/2076-3417/11/11/4725 https://doi.org/10.3390/app11114725 https://doi.org/10.3390/app11114725 |
| spellingShingle | QA Mathematics T Technology (General) Kashif Nisar Zulqurnain Sabir Muhammad Asif Zahoor Raja Ag. Asri Ag. Ibrahim Joel J. P. C. Rodrigues Adnan Shahid Khan Manoj Gupta Aldawoud Kamal Danda B. Rawat Evolutionary integrated heuristic with gudermannian neural networks for second kind of lane– emden nonlinear singular models |
| title | Evolutionary integrated heuristic with gudermannian neural networks for second kind of lane– emden nonlinear singular models |
| title_full | Evolutionary integrated heuristic with gudermannian neural networks for second kind of lane– emden nonlinear singular models |
| title_fullStr | Evolutionary integrated heuristic with gudermannian neural networks for second kind of lane– emden nonlinear singular models |
| title_full_unstemmed | Evolutionary integrated heuristic with gudermannian neural networks for second kind of lane– emden nonlinear singular models |
| title_short | Evolutionary integrated heuristic with gudermannian neural networks for second kind of lane– emden nonlinear singular models |
| title_sort | evolutionary integrated heuristic with gudermannian neural networks for second kind of lane emden nonlinear singular models |
| topic | QA Mathematics T Technology (General) |
| url | https://eprints.ums.edu.my/id/eprint/30009/1/Evolutionary%20integrated%20heuristic%20with%20gudermannian%20neural%20networks%20for%20second%20kind%20of%20lane%E2%80%93emden%20nonlinear%20singular%20models-Abstract.pdf https://eprints.ums.edu.my/id/eprint/30009/2/Evolutionary%20integrated%20heuristic%20with%20gudermannian%20neural%20networks%20for%20second%20kind%20of%20lane%E2%80%93emden%20nonlinear%20singular%20models.pdf |
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