Abstract
A vague relation, as well as an intuitionistic fuzzy relation, is a further generalization of a fuzzy relation. In fact there are situations where vague relations are more appropriate. In this paper, fuzzy clustering based on vague relations is investigate. On the basis of max-t & min-s compositions, we make a further extension of n-step procedure. With the proposed n-step procedure, a similarity vague relation matrix is obtained by beginning with a proximity vague relation matrix. Then a clustering algorithm is proposed for the similarity vague relation matrix.
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Zhao, F., Ma, Z.M., Yan, L. (2006). Fuzzy Clustering Based on Vague Relations. In: Wang, L., Jiao, L., Shi, G., Li, X., Liu, J. (eds) Fuzzy Systems and Knowledge Discovery. FSKD 2006. Lecture Notes in Computer Science(), vol 4223. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11881599_10
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DOI: https://doi.org/10.1007/11881599_10
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-45916-3
Online ISBN: 978-3-540-45917-0
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