Hybrid expert system of rough set and neural network
The combination of neural network and expert system can accelerate the process of inference, and then rapidly produce associated facts and consequences. However, neural network still has some problems such as providing explanation facilities, managing the architecture of network and accelerating the...
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Faculty of Computer Science and Information Technology, University of Malaya
1999
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Online Access: | http://psasir.upm.edu.my/id/eprint/49451/1/Hybrid%20expert%20system%20of%20rough%20set%20and%20neural%20network.pdf http://psasir.upm.edu.my/id/eprint/49451/ http://e-journal.um.edu.my/publish/MJCS/136-150 |
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my.upm.eprints.494512016-12-30T02:49:23Z http://psasir.upm.edu.my/id/eprint/49451/ Hybrid expert system of rough set and neural network Yahia, Moawia Elfaki Mahmod, Ramlan The combination of neural network and expert system can accelerate the process of inference, and then rapidly produce associated facts and consequences. However, neural network still has some problems such as providing explanation facilities, managing the architecture of network and accelerating the training time. Thus to address these issues we develop a new method for pre-processing based on rough set and merge it with neural network and expert system. The resulting system is a hybrid expert system model called a Hybrid Rough Neural Expert System (HRNES). Faculty of Computer Science and Information Technology, University of Malaya 1999 Article PeerReviewed application/pdf en http://psasir.upm.edu.my/id/eprint/49451/1/Hybrid%20expert%20system%20of%20rough%20set%20and%20neural%20network.pdf Yahia, Moawia Elfaki and Mahmod, Ramlan (1999) Hybrid expert system of rough set and neural network. Malaysian Journal of Computer Science, 12 (1). pp. 1-8. ISSN 0127-9084 http://e-journal.um.edu.my/publish/MJCS/136-150 |
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The combination of neural network and expert system can accelerate the process of inference, and then rapidly produce associated facts and consequences. However, neural network still has some problems such as providing explanation facilities, managing the architecture of network and accelerating the training time. Thus to address these issues we develop a new method for pre-processing based on rough set and merge it with neural network and expert system. The resulting system is a hybrid expert system model called a Hybrid Rough Neural Expert System (HRNES). |
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Article |
author |
Yahia, Moawia Elfaki Mahmod, Ramlan |
spellingShingle |
Yahia, Moawia Elfaki Mahmod, Ramlan Hybrid expert system of rough set and neural network |
author_facet |
Yahia, Moawia Elfaki Mahmod, Ramlan |
author_sort |
Yahia, Moawia Elfaki |
title |
Hybrid expert system of rough set and neural network |
title_short |
Hybrid expert system of rough set and neural network |
title_full |
Hybrid expert system of rough set and neural network |
title_fullStr |
Hybrid expert system of rough set and neural network |
title_full_unstemmed |
Hybrid expert system of rough set and neural network |
title_sort |
hybrid expert system of rough set and neural network |
publisher |
Faculty of Computer Science and Information Technology, University of Malaya |
publishDate |
1999 |
url |
http://psasir.upm.edu.my/id/eprint/49451/1/Hybrid%20expert%20system%20of%20rough%20set%20and%20neural%20network.pdf http://psasir.upm.edu.my/id/eprint/49451/ http://e-journal.um.edu.my/publish/MJCS/136-150 |
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