Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor | Multi-disciplinary Studies | en_US |
| dc.contributor | Department of Computing | en_US |
| dc.creator | Wong, Chak-wing | - |
| dc.identifier.uri | https://theses.lib.polyu.edu.hk/handle/200/770 | - |
| dc.language | English | en_US |
| dc.publisher | Hong Kong Polytechnic University | - |
| dc.rights | All rights reserved | en_US |
| dc.title | Fuzzy rule extraction from neural network | en_US |
| dcterms.abstract | Neural Network has been successfully applied in a wide range of applications. However, the neural network is non-transparent and provides no explanatory capability support for a given output. In this paper, we examine the properties concerning the Causal Index Technique for extracting fuzzy rules from a multiple layered neural network. Specially, this paper focuses on the fundamental algorithm, prototype development method, stepwise case simulation approach and the analysis of various empirical results. Finally the strengths and weakness in relation to the Causal Index Technique are examined. | en_US |
| dcterms.extent | 135 leaves : ill. ; 30 cm | en_US |
| dcterms.isPartOf | PolyU Electronic Theses | en_US |
| dcterms.issued | 1998 | en_US |
| dcterms.educationalLevel | All Master | en_US |
| dcterms.educationalLevel | M.Sc. | en_US |
| dcterms.LCSH | Fuzzy systems | en_US |
| dcterms.LCSH | Neural networks (Computer science) | en_US |
| dcterms.LCSH | Hong Kong Polytechnic University -- Dissertations | en_US |
| dcterms.accessRights | restricted access | en_US |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| b1436931x.pdf | For All Users (off-campus access for PolyU Staff & Students only) | 3.9 MB | Adobe PDF | View/Open |
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