In this paper, we define hesitant fuzzy partitions (H-fuzzy partitions) to consider the results of standard fuzzy clustering family (e.g. fuzzy c-means and intuitionistic fuzzy c-means). We define a method to construct H-fuzzy partitions from a set of fuzzy clusters obtained from several executions of fuzzy clustering algorithms with various initialization of their parameters. Our purpose is to consider some local optimal solutions to find a global optimal solution also letting the user to consider various reliable membership values and cluster centers to evaluate her/his problem using different cluster validity indices.
CITATION STYLE
Aliahmadipour, L., Torra, V., Eslami, E., & Eftekhari, M. (2016). A Definition for Hesitant fuzzy Partitions. International Journal of Computational Intelligence Systems, 9(3), 497–505. https://doi.org/10.1080/18756891.2016.1175814
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