Journal of Operational Research and Its Applications ( Applied Mathematics ) - Lahijan Azad University

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One of the main issues in fuzzy clustering is to determine the number of clusters that should be available before clustering and selection of different values for the number of clusters will lead to different results. Then, different clusters obtained from different number of clusters should be validated with an index. But so far such an index has not been introduced for interval type-2 fuzzy C-means (IT-2 FCM), and when using this algorithm, common indices are used to determine the number of clusters, and these values are also considered constant and general. we will introduce an index to test the validity of these algorithms in this paper. Then, after an overview of clustering validation indices and related researches, the volatility of these indices for use in IT-2 FCM is shown. The results of the implementation of the proposed index on the four data sets show that by using the suggested index, the volatility and bugs of common indices have been fixed due to obtaining optimal interval. Using suggested index could have a significant effect on type-2 controllers (type-2 fuzzy logic systems) and improve forecast results and control in these systems.
 

Keywords: Clustering Validation Index, Fuzzy Clustering, IT2 FCM.

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