On Computing Cluster Centers of Trapezoidal Fuzzy Numbers
S. Sreenivasan1, B. J. Balamurugan2
1S. Sreenivasan, Department of Advanced Sciences, VIT University, Chennai Campus, Chennai (Tamil Nadu), India.
2B. J. Balamurugan, Department of Advanced Sciences, VIT University, Chennai Campus, Chennai (Tamil Nadu), India.
Manuscript received on 16 December 2019 | Revised Manuscript received on 23 December 2019 | Manuscript Published on 31 December 2019 | PP: 356-359 | Volume-9 Issue-1S3 December 2019 | Retrieval Number: A10671291S319/19©BEIESP | DOI: 10.35940/ijeat.A1067.1291S319
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: In this paper we compute cluster centers of trapezoidal fuzzy numbers through fuzzy c means clustering algorithm and kernel based fuzzy c means clustering algorithm. A new complete metric distance between the trapezoidal fuzzy numbers is used to compute the cluster centers on the set of trapezoidal fuzzy numbers.
Keywords: Fuzzy Clustering, Kernel Function, Trapezoidal Fuzzy Numbers, Fuzzy C Number Clustering Algorithms.
Scope of the Article: Autonomic Computing