A New Clustering Method with Fuzzy Approach Based on Takagi-Sugeno Model in Queuing Systems

Farzaneh Gholami Zanjanbar and Inci Sentarli
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Farzaneh Gholami Zanjanbar: Department of Management, Çankaya University, Ankara, Turkey
Inci Sentarli: Department of Management, Çankaya University, Ankara, Turkey

International Journal of Fuzzy System Applications (IJFSA), 2013, vol. 3, issue 2, 32-54

Abstract: In this paper, the authors propose a new hard clustering method to provide objective knowledge on field of fuzzy queuing system. In this method, locally linear controllers are extracted and translated into the first-order Takagi-Sugeno rule base fuzzy model. In this extraction process, the region of fuzzy subspaces of available inputs corresponding to different implications is used to obtain the clusters of outputs of the queuing system. Then, the multiple regression functions associated with these separate clusters are used to interpret the performance of queuing systems. An application of the method also is presented and the performance of the queuing system is discussed.

Date: 2013
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Persistent link: https://EconPapers.repec.org/RePEc:igg:jfsa00:v:3:y:2013:i:2:p:32-54

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