Abstract
In this paper, we discuss preciseness of data in terms of obtaining degree of similarity in which fuzzy set can be used as an alternative to represent imprecise data. Degree of similarity between two imprecise data represented in two fuzzy sets is approximately determined by using fuzzy conditional probability relation. Moreover, degree of similarity relationship between fuzzy sets corresponding to fuzzy classes as results of fuzzy partition on a given finite set of data is examined. Related to a well known fuzzy partition, called fuzzy pseudopartition or fuzzy c-partition where c designates the number of fuzzy classes in the partition, we introduce fuzzy symmetric c-partition regarded as a special case of the fuzzy c-partition. In addition, we also introduce fuzzy covering as a generalization of fuzzy partition. Similarly, two fuzzy coverings, namely fuzzy c-covering and fuzzy symmetric c-covering are proposed corresponding to fuzzy c-partition and fuzzy symmetric c-partition, respectively.
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Intan, R., Mukaidono, M. (2002). Degree of Similarity in Fuzzy Partition. In: Pal, N.R., Sugeno, M. (eds) Advances in Soft Computing — AFSS 2002. AFSS 2002. Lecture Notes in Computer Science(), vol 2275. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45631-7_3
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DOI: https://doi.org/10.1007/3-540-45631-7_3
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