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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Main Authors: Yahia, Moawia Elfaki, Mahmod, Ramlan
Format: Article
Language:English
Published: Faculty of Computer Science and Information Technology, University of Malaya 1999
Online Access:http://psasir.upm.edu.my/id/eprint/49451/
http://psasir.upm.edu.my/id/eprint/49451/1/Hybrid%20expert%20system%20of%20rough%20set%20and%20neural%20network.pdf
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author Yahia, Moawia Elfaki
Mahmod, Ramlan
author_facet Yahia, Moawia Elfaki
Mahmod, Ramlan
author_sort Yahia, Moawia Elfaki
building UPM Institutional Repository
collection Online Access
description 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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institution Universiti Putra Malaysia
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language English
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publishDate 1999
publisher Faculty of Computer Science and Information Technology, University of Malaya
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spelling upm-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
spellingShingle Yahia, Moawia Elfaki
Mahmod, Ramlan
Hybrid expert system of rough set and neural network
title 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_short Hybrid expert system of rough set and neural network
title_sort hybrid expert system of rough set and neural network
url http://psasir.upm.edu.my/id/eprint/49451/
http://psasir.upm.edu.my/id/eprint/49451/
http://psasir.upm.edu.my/id/eprint/49451/1/Hybrid%20expert%20system%20of%20rough%20set%20and%20neural%20network.pdf