Perbandingan penggunaan algoritma Krzyzak dengan algoritma rambatan balik piawai dalam domain peramalan
The purpose of this study is to compare the performance of neural network using Krzyzak algorithm and standard back propagation algorithm in forecasting domain. To implement this study a timber data set, which represents a non-seasonal time series data, is used. The performance is measured based on...
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Universiti Utara Malaysia
2004
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| Online Access: | http://eprints.utm.my/3432/ http://repo.uum.edu.my/272/ |
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| author | Alwee, Razana Sallehuddin, Roselina Shamsuddin, Siti Mariyam |
| author_facet | Alwee, Razana Sallehuddin, Roselina Shamsuddin, Siti Mariyam |
| author_sort | Alwee, Razana |
| building | UTM Library |
| collection | Institutional Repository |
| content_provider | Universiti Teknologi Malaysia |
| content_source | UTM Institutional Repository |
| continent | Asia |
| country | Malaysia |
| description | The purpose of this study is to compare the performance of neural network using Krzyzak algorithm and standard back propagation algorithm in forecasting domain. To implement this study a timber data set, which represents a non-seasonal time series data, is used. The performance is measured based on the accuracies, which is, quantified by root mean square error and learning speed for convergence. The results show that by using a small value of learning rate, Krzyzak algorithm is better than standard back propagation algorithm for medium and long term forecasting. |
| format | Article |
| id | my.utm.eprints-3432 |
| institution | Universiti Teknologi Malaysia |
| publishDate | 2004 |
| publisher | Universiti Utara Malaysia |
| record_format | eprints |
| spelling | my.utm.eprints-34322018-03-07T20:52:14Z http://eprints.utm.my/3432/ Perbandingan penggunaan algoritma Krzyzak dengan algoritma rambatan balik piawai dalam domain peramalan Alwee, Razana Sallehuddin, Roselina Shamsuddin, Siti Mariyam QA Mathematics The purpose of this study is to compare the performance of neural network using Krzyzak algorithm and standard back propagation algorithm in forecasting domain. To implement this study a timber data set, which represents a non-seasonal time series data, is used. The performance is measured based on the accuracies, which is, quantified by root mean square error and learning speed for convergence. The results show that by using a small value of learning rate, Krzyzak algorithm is better than standard back propagation algorithm for medium and long term forecasting. Universiti Utara Malaysia 2004-02 Article PeerReviewed Alwee, Razana and Sallehuddin, Roselina and Shamsuddin, Siti Mariyam (2004) Perbandingan penggunaan algoritma Krzyzak dengan algoritma rambatan balik piawai dalam domain peramalan. International Journal of Management Studies, 11 . pp. 171-183. http://repo.uum.edu.my/272/ |
| spellingShingle | QA Mathematics Alwee, Razana Sallehuddin, Roselina Shamsuddin, Siti Mariyam Perbandingan penggunaan algoritma Krzyzak dengan algoritma rambatan balik piawai dalam domain peramalan |
| title | Perbandingan penggunaan algoritma Krzyzak dengan algoritma rambatan balik piawai dalam domain peramalan |
| title_full | Perbandingan penggunaan algoritma Krzyzak dengan algoritma rambatan balik piawai dalam domain peramalan |
| title_fullStr | Perbandingan penggunaan algoritma Krzyzak dengan algoritma rambatan balik piawai dalam domain peramalan |
| title_full_unstemmed | Perbandingan penggunaan algoritma Krzyzak dengan algoritma rambatan balik piawai dalam domain peramalan |
| title_short | Perbandingan penggunaan algoritma Krzyzak dengan algoritma rambatan balik piawai dalam domain peramalan |
| title_sort | perbandingan penggunaan algoritma krzyzak dengan algoritma rambatan balik piawai dalam domain peramalan |
| topic | QA Mathematics |
| url | http://eprints.utm.my/3432/ http://repo.uum.edu.my/272/ |
| url_provider | http://eprints.utm.my/ |