Hybrib NSGA-II optimization for improving the three-term BP network for multiclass classification problems
Recently, hybrid algorithms have received considerable attention from a number of researchers. This paper presents a hybrid of the multiobjective evolutionary algorithm to gain a better accuracy of the fi nal solutions.The aim of using the hybrid algorithm is to improve the multiobjective evolutiona...
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| Format: | Article |
| Language: | English |
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Universiti Utara Malaysia Press
2015
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| Online Access: | https://repo.uum.edu.my/id/eprint/24080/1/JICT%2014%202015%2021%E2%80%9338.pdf |
| _version_ | 1825805042914951168 |
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| author | Ibrahim, Ashraf Osman Shamsuddin, Siti Mariyam Qasem, Sultan Noman |
| author_facet | Ibrahim, Ashraf Osman Shamsuddin, Siti Mariyam Qasem, Sultan Noman |
| author_sort | Ibrahim, Ashraf Osman |
| collection | UUM |
| description | Recently, hybrid algorithms have received considerable attention from a number of researchers. This paper presents a hybrid of the multiobjective evolutionary algorithm to gain a better accuracy of the fi nal solutions.The aim of using the hybrid algorithm is to improve the multiobjective evolutionary algorithm performance in terms of the enhancement of all the individuals in the population and increase the quality of the Pareto optimal solutions.The multiobjective evolutionary algorithm used in this study is a nondominated sorting genetic algorithm-II (NSGA-II) together with its hybrid, the backpropagation algorithm (BP), which is used as a local search algorithm to optimize the accuracy and complexity of the three-term backpropagation (TBP) network. The outcome positively demonstrates that the hybrid algorithm is able to improve the classification performance with a smaller number of hidden nodes and is effective in multiclass classifi cation problems.Furthermore, the results indicate that the proposed hybrid method is a potentially useful classifi er for enhancing the classification process ability when compared with the multiobjective genetic algorithm based on the TBP network (MOGATBP) and certain other methods found in the literature. |
| first_indexed | 2024-07-04T06:25:26Z |
| format | Article |
| id | uum-24080 |
| institution | Universiti Utara Malaysia |
| language | English |
| last_indexed | 2024-07-04T06:25:26Z |
| publishDate | 2015 |
| publisher | Universiti Utara Malaysia Press |
| record_format | eprints |
| spelling | uum-240802018-04-29T01:43:56Z https://repo.uum.edu.my/id/eprint/24080/ Hybrib NSGA-II optimization for improving the three-term BP network for multiclass classification problems Ibrahim, Ashraf Osman Shamsuddin, Siti Mariyam Qasem, Sultan Noman QA75 Electronic computers. Computer science Recently, hybrid algorithms have received considerable attention from a number of researchers. This paper presents a hybrid of the multiobjective evolutionary algorithm to gain a better accuracy of the fi nal solutions.The aim of using the hybrid algorithm is to improve the multiobjective evolutionary algorithm performance in terms of the enhancement of all the individuals in the population and increase the quality of the Pareto optimal solutions.The multiobjective evolutionary algorithm used in this study is a nondominated sorting genetic algorithm-II (NSGA-II) together with its hybrid, the backpropagation algorithm (BP), which is used as a local search algorithm to optimize the accuracy and complexity of the three-term backpropagation (TBP) network. The outcome positively demonstrates that the hybrid algorithm is able to improve the classification performance with a smaller number of hidden nodes and is effective in multiclass classifi cation problems.Furthermore, the results indicate that the proposed hybrid method is a potentially useful classifi er for enhancing the classification process ability when compared with the multiobjective genetic algorithm based on the TBP network (MOGATBP) and certain other methods found in the literature. Universiti Utara Malaysia Press 2015 Article PeerReviewed application/pdf en https://repo.uum.edu.my/id/eprint/24080/1/JICT%2014%202015%2021%E2%80%9338.pdf Ibrahim, Ashraf Osman and Shamsuddin, Siti Mariyam and Qasem, Sultan Noman (2015) Hybrib NSGA-II optimization for improving the three-term BP network for multiclass classification problems. Journal of Information and Communication Technology, 14. pp. 21-38. ISSN 2180-3862 http://jict.uum.edu.my/index.php/previous-issues/143-vol-14-2015 |
| spellingShingle | QA75 Electronic computers. Computer science Ibrahim, Ashraf Osman Shamsuddin, Siti Mariyam Qasem, Sultan Noman Hybrib NSGA-II optimization for improving the three-term BP network for multiclass classification problems |
| title | Hybrib NSGA-II optimization for improving the three-term BP network for multiclass classification problems |
| title_full | Hybrib NSGA-II optimization for improving the three-term BP network for multiclass classification problems |
| title_fullStr | Hybrib NSGA-II optimization for improving the three-term BP network for multiclass classification problems |
| title_full_unstemmed | Hybrib NSGA-II optimization for improving the three-term BP network for multiclass classification problems |
| title_short | Hybrib NSGA-II optimization for improving the three-term BP network for multiclass classification problems |
| title_sort | hybrib nsga ii optimization for improving the three term bp network for multiclass classification problems |
| topic | QA75 Electronic computers. Computer science |
| url | https://repo.uum.edu.my/id/eprint/24080/1/JICT%2014%202015%2021%E2%80%9338.pdf |
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