title   
  

A new fuzzy inference approach based on Mamdani inference using discrete type 2 fuzzy sets

Uncu, Özge and Kılıç, Kemal and Turksen, I. B. A new fuzzy inference approach based on Mamdani inference using discrete type 2 fuzzy sets. In: IEEE International Conference on Systems, Man and Cybernetics, 2004, The Hague, Netherlands

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Official URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=01400667

Abstract

Fuzzy system modeling (FSM) is one of the most prominent system modeling tools in analyzing the data in the presence of uncertainty. Linguistic fuzzy rulebase (LFR) structure, in which both the antecedent and consequent variables are represented by fuzzy sets, is the most well known fuzzy rulebase structure in the literature. The proposed FSM method identifies LFR system model by executing fuzzy C-Means (FCM) clustering method. One of the sources of uncertainty in system modeling is the uncertainty in selecting learning parameters. In order to capture this uncertainty in a more realistic way, the antecedent and consequent variables are represented by using type 2 fuzzy sets that are constructed by executing FCM method with different level of fuzziness, m, values. The proposed system modeling approach is applied on a well-known benchmark data set where the goal is to predict the price of a stock. After comparing the results with the ones obtained with other system modeling tools, it can be claimed successful results are achieved.

Item Type:Papers in Conference Proceedings
Additional Information:ISI:000226863300381
Uncontrolled Keywords:fuzzy reasoning fuzzy set theory fuzzy systems Mamdani inference discrete type 2 fuzzy sets fuzzy C-means clustering method fuzzy inference approach fuzzy system modeling linguistic fuzzy rulebase structure
Subjects:T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK7800-8360 Electronics
ID Code:1401
Deposited By:Kemal Kılıç
Deposited On:31 Dec 2004 02:00
Last Modified:25 Jul 2009 22:01

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