Hybridization of the swarming and interior point algorithms to solve the Rabinovich–Fabrikant system
Abstract In this study, a trustworthy swarming computing procedure is demonstrated for solving the nonlinear dynamics of the Rabinovich–Fabrikant system. The nonlinear system’s dynamic depends upon the three differential equations. The computational stochastic structure based on the artificial neura...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2023-07-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-023-37466-6 |
| _version_ | 1797784606868504576 |
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| author | Zulqurnain Sabir Salem Ben Said Qasem Al-Mdallal |
| author_facet | Zulqurnain Sabir Salem Ben Said Qasem Al-Mdallal |
| author_sort | Zulqurnain Sabir |
| collection | DOAJ |
| description | Abstract In this study, a trustworthy swarming computing procedure is demonstrated for solving the nonlinear dynamics of the Rabinovich–Fabrikant system. The nonlinear system’s dynamic depends upon the three differential equations. The computational stochastic structure based on the artificial neural networks (ANNs) along with the optimization of global search swarming particle swarm optimization (PSO) and local interior point (IP) algorithms, i.e., ANNs-PSOIP is presented to solve the Rabinovich–Fabrikant system. An objective function based on the differential form of the model is optimized through the local and global search methods. The correctness of the ANNs-PSOIP scheme is observed through the performances of achieved and source solutions, while the negligible absolute error that is around 10−05–10−07 also represent the worth of the ANNs-PSOIP algorithm. Furthermore, the consistency of the ANNs-PSOIP scheme is examined by applying different statistical procedures to solve the Rabinovich–Fabrikant system. |
| first_indexed | 2024-03-13T00:42:19Z |
| format | Article |
| id | doaj.art-1bda882a53894ca3ab6251289e57860e |
| institution | Directory Open Access Journal |
| issn | 2045-2322 |
| language | English |
| last_indexed | 2024-03-13T00:42:19Z |
| publishDate | 2023-07-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj.art-1bda882a53894ca3ab6251289e57860e2023-07-09T11:12:16ZengNature PortfolioScientific Reports2045-23222023-07-0113111310.1038/s41598-023-37466-6Hybridization of the swarming and interior point algorithms to solve the Rabinovich–Fabrikant systemZulqurnain Sabir0Salem Ben Said1Qasem Al-Mdallal2Department of Mathematical Sciences, College of Science, United Arab Emirates UniversityDepartment of Mathematical Sciences, College of Science, United Arab Emirates UniversityDepartment of Mathematical Sciences, College of Science, United Arab Emirates UniversityAbstract In this study, a trustworthy swarming computing procedure is demonstrated for solving the nonlinear dynamics of the Rabinovich–Fabrikant system. The nonlinear system’s dynamic depends upon the three differential equations. The computational stochastic structure based on the artificial neural networks (ANNs) along with the optimization of global search swarming particle swarm optimization (PSO) and local interior point (IP) algorithms, i.e., ANNs-PSOIP is presented to solve the Rabinovich–Fabrikant system. An objective function based on the differential form of the model is optimized through the local and global search methods. The correctness of the ANNs-PSOIP scheme is observed through the performances of achieved and source solutions, while the negligible absolute error that is around 10−05–10−07 also represent the worth of the ANNs-PSOIP algorithm. Furthermore, the consistency of the ANNs-PSOIP scheme is examined by applying different statistical procedures to solve the Rabinovich–Fabrikant system.https://doi.org/10.1038/s41598-023-37466-6 |
| spellingShingle | Zulqurnain Sabir Salem Ben Said Qasem Al-Mdallal Hybridization of the swarming and interior point algorithms to solve the Rabinovich–Fabrikant system Scientific Reports |
| title | Hybridization of the swarming and interior point algorithms to solve the Rabinovich–Fabrikant system |
| title_full | Hybridization of the swarming and interior point algorithms to solve the Rabinovich–Fabrikant system |
| title_fullStr | Hybridization of the swarming and interior point algorithms to solve the Rabinovich–Fabrikant system |
| title_full_unstemmed | Hybridization of the swarming and interior point algorithms to solve the Rabinovich–Fabrikant system |
| title_short | Hybridization of the swarming and interior point algorithms to solve the Rabinovich–Fabrikant system |
| title_sort | hybridization of the swarming and interior point algorithms to solve the rabinovich fabrikant system |
| url | https://doi.org/10.1038/s41598-023-37466-6 |
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