Accelerating learning performance of back propagation algorithm by using adaptive gain together with adaptive momentum and adaptive learning rate on classification problems
The back propagation (BP) algorithm is a very popular learning approach in feedforward multilayer perceptron networks. However, the most serious problem associated with the BP is local minima problem and slow convergence speeds. Over the years, many improvements and modifications of the back...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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2011
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| Online Access: | http://eprints.uthm.edu.my/7955/ http://eprints.uthm.edu.my/7955/1/J3714_e277896270c61202b64daf13c7d0f992.pdf |
| _version_ | 1848889256029716480 |
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| author | Abdul Hamid, Norhamreeza Mohd Nawi, Nazri Ghazali, Rozaida Mohd Salleh, Mohd Najib |
| author_facet | Abdul Hamid, Norhamreeza Mohd Nawi, Nazri Ghazali, Rozaida Mohd Salleh, Mohd Najib |
| author_sort | Abdul Hamid, Norhamreeza |
| building | UTHM Institutional Repository |
| collection | Online Access |
| description | The back propagation (BP) algorithm is a very popular learning
approach in feedforward multilayer perceptron networks. However, the most
serious problem associated with the BP is local minima problem and slow
convergence speeds. Over the years, many improvements and modifications of
the back propagation learning algorithm have been reported. In this research,
we propose a new modified back propagation learning algorithm by introducing
adaptive gain together with adaptive momentum and adaptive learning rate into
weight update process. By computer simulations, we demonstrate that the
proposed algorithm can give a better convergence rate and can find a good
solution in early time compare to the conventional back propagation. We use
two common benchmark classification problems to illustrate the improvement
in convergence time. |
| first_indexed | 2025-11-15T20:23:17Z |
| format | Article |
| id | uthm-7955 |
| institution | Universiti Tun Hussein Onn Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T20:23:17Z |
| publishDate | 2011 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | uthm-79552022-11-02T06:43:43Z http://eprints.uthm.edu.my/7955/ Accelerating learning performance of back propagation algorithm by using adaptive gain together with adaptive momentum and adaptive learning rate on classification problems Abdul Hamid, Norhamreeza Mohd Nawi, Nazri Ghazali, Rozaida Mohd Salleh, Mohd Najib T Technology (General) The back propagation (BP) algorithm is a very popular learning approach in feedforward multilayer perceptron networks. However, the most serious problem associated with the BP is local minima problem and slow convergence speeds. Over the years, many improvements and modifications of the back propagation learning algorithm have been reported. In this research, we propose a new modified back propagation learning algorithm by introducing adaptive gain together with adaptive momentum and adaptive learning rate into weight update process. By computer simulations, we demonstrate that the proposed algorithm can give a better convergence rate and can find a good solution in early time compare to the conventional back propagation. We use two common benchmark classification problems to illustrate the improvement in convergence time. 2011 Article PeerReviewed text en http://eprints.uthm.edu.my/7955/1/J3714_e277896270c61202b64daf13c7d0f992.pdf Abdul Hamid, Norhamreeza and Mohd Nawi, Nazri and Ghazali, Rozaida and Mohd Salleh, Mohd Najib (2011) Accelerating learning performance of back propagation algorithm by using adaptive gain together with adaptive momentum and adaptive learning rate on classification problems. International Journal of Software Engineering and its Applications, 5 (4). pp. 31-44. https://doi.org/10.1007/978-3-642-20998-7_62 |
| spellingShingle | T Technology (General) Abdul Hamid, Norhamreeza Mohd Nawi, Nazri Ghazali, Rozaida Mohd Salleh, Mohd Najib Accelerating learning performance of back propagation algorithm by using adaptive gain together with adaptive momentum and adaptive learning rate on classification problems |
| title | Accelerating learning performance of back propagation algorithm by using adaptive gain together with adaptive momentum and adaptive learning rate on classification problems |
| title_full | Accelerating learning performance of back propagation algorithm by using adaptive gain together with adaptive momentum and adaptive learning rate on classification problems |
| title_fullStr | Accelerating learning performance of back propagation algorithm by using adaptive gain together with adaptive momentum and adaptive learning rate on classification problems |
| title_full_unstemmed | Accelerating learning performance of back propagation algorithm by using adaptive gain together with adaptive momentum and adaptive learning rate on classification problems |
| title_short | Accelerating learning performance of back propagation algorithm by using adaptive gain together with adaptive momentum and adaptive learning rate on classification problems |
| title_sort | accelerating learning performance of back propagation algorithm by using adaptive gain together with adaptive momentum and adaptive learning rate on classification problems |
| topic | T Technology (General) |
| url | http://eprints.uthm.edu.my/7955/ http://eprints.uthm.edu.my/7955/ http://eprints.uthm.edu.my/7955/1/J3714_e277896270c61202b64daf13c7d0f992.pdf |