A New Fuzzy Inference Method for Systems with Large Number of Rules
| contributor author | هدی مودی | en |
| contributor author | دانیال بوستان | en |
| contributor author | حبیب رجبی مشهدی | en |
| contributor author | Danyal Bustan | fa |
| contributor author | Habib Rajabi Mashhadi | fa |
| date accessioned | 2020-06-06T13:55:38Z | |
| date available | 2020-06-06T13:55:38Z | |
| date copyright | 5/17/2006 | |
| date issued | 2006 | |
| identifier uri | https://libsearch.um.ac.ir:443/fum/handle/fum/3375082?show=full | |
| description abstract | In this paper, a new fuzzy inference method which is suitable for systems with large number of rules, is proposed. As we know, there are two well-known fuzzy inference systems, Mamdani and TSK. Each one has its own drawbacks and advantages but both of them have been encountered with problem while tuning their parameters especially when there is large number of rules in the system. Mamdani type systems faced to a huge amount of calculation and TSK type faced to large number of parameters. In our proposed method a combination of these two systems, is used. So it has small number of parameters for tuning as Mamdani has and it is as fast as TSK. We called this system Extended TSK because it is based upon it. | en |
| language | English | |
| title | A New Fuzzy Inference Method for Systems with Large Number of Rules | en |
| type | Conference Paper | |
| contenttype | External Fulltext | |
| subject keywords | Fuzzy modeling | en |
| subject keywords | parameter tuning | en |
| identifier link | https://profdoc.um.ac.ir/paper-abstract-1013198.html | |
| conference title | ششمین کنفرانس سیستم های فازی ایران | fa |
| identifier articleid | 1013198 |
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