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A hierarchy-based similarity measure for intuitionistic fuzzy sets

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Abstract

Due to some unreasonable results obtained from most current similarity measures for intuitionistic fuzzy sets (IFSs), we introduce a necessary condition to obtain a stronger definition of similarity measures for IFSs, and present a new similarity measure derived from a general idea of similarity measures for concepts on a lattice. In experiments, we focus our attention on two basic directions of performance evaluation: one is how much the proposed measure is reasonable and the other is how much accuracy the measure produces when it is applied to classification problems. The experimental results show that the proposed measure is reasonable and achieves a satisfactory performance on classification problems.

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Notes

  1. A partial order on a nonempty set \(P\) is a binary relation on \(P\) satisfying reflexivity, antisymmetry, and transitivity.

  2. Available at http://sci2s.ugr.es/keel.

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Acknowledgments

The author thanks the anonymous referees for very useful suggestion to improve this paper and gratefully acknowledges the financial support provided by Thammasat University Research Fund under the TU Research Scholar, Contract No. 1/8/2557.

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I certify that there is no actual or potential conflict of interest in relation to this article.

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Authors and Affiliations

  1. Department of Mathematics and Statistics, Faculty of Science and Technology, Thammasat University, Pathum Thani, 12121, Thailand

    Peerasak Intarapaiboon

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  1. Peerasak Intarapaiboon
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Correspondence to Peerasak Intarapaiboon.

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Communicated by V. Loia.

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Intarapaiboon, P. A hierarchy-based similarity measure for intuitionistic fuzzy sets. Soft Comput 20, 1909–1919 (2016). https://doi.org/10.1007/s00500-015-1612-x

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