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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Young Im Cho |
| Copyright Year | 2007 |
| Description | Author affiliation: Univ. of Suwon, Seoul (Young Im Cho) |
| Abstract | A conventional fuzzy control system has some problems in compositional rule of inference. Therefore, it produces a big error for a premise which is very similar or identical to one of premises in rules. It is because the importance of rules is not taken into the consideration for inference. To overcome of the problem, we propose an improved fuzzy inference algorithm to reduce the error by providing weights to composition of rules according to the similarity of premises. We show that the proposed similarity measure can reduce a lot of error regions compared with the conventional fuzzy inference method using the example of a fuzzy controller. |
| Starting Page | 463 |
| Ending Page | 466 |
| File Size | 1075168 |
| Page Count | 4 |
| File Format | |
| ISBN | 9788995003862 |
| DOI | 10.1109/ICCAS.2007.4406952 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2007-10-17 |
| Publisher Place | South Korea |
| Access Restriction | Subscribed |
| Rights Holder | ICASE |
| Subject Keyword | Automation fuzzy inference Control systems Superluminescent diodes Fuzzy controller Fuzzy control Weight control weighted algorithm Automatic control Inference algorithms Error correction Mathematical model Fuzzy systems |
| Content Type | Text |
| Resource Type | Article |
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