In the literature we find two different approaches to define entropies of AIFSs. On the one hand, Szmidt and Kacprzyk’s entropy measures how far is an AIFS from a crisp set; on the other hand, Burrillo and Bustince’s approach measures how far is an AIFS from a fuzzy set. In this work we use divergence measures to define both types of entropies. We also show the conditions that we must impose on the divergence to define entropy measures of AIFSs and use our results to build several examples.
CITATION STYLE
Montes, I., Montes, S., & Pal, N. (2018). On the use of divergences for defining entropies for atanassov intuitionistic fuzzy sets. In Advances in Intelligent Systems and Computing (Vol. 642, pp. 554–565). Springer Verlag. https://doi.org/10.1007/978-3-319-66824-6_49
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