| Author: | Wong, Chak-wing |
| Title: | Fuzzy rule extraction from neural network |
| Degree: | M.Sc. |
| Year: | 1998 |
| Subject: | Fuzzy systems Neural networks (Computer science) Hong Kong Polytechnic University -- Dissertations |
| Department: | Multi-disciplinary Studies Department of Computing |
| Pages: | 135 leaves : ill. ; 30 cm |
| Language: | English |
| 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. |
| Rights: | All rights reserved |
| Access: | restricted access |
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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