Fuzzy Sets and Systems
Some remarks on distances between fuzzy numbers
Fuzzy Sets and Systems
Distances between fuzzy sets representing grey level images
Fuzzy Sets and Systems
Distances between intuitionistic fuzzy sets
Fuzzy Sets and Systems
Fuzzy clustering with squared Minkowski distances
Fuzzy Sets and Systems - Special issue on clustering and learning
Reasoning About Distance Based on Fuzzy Sets
Applied Intelligence
New similarity measures of intuitionistic fuzzy sets and application to pattern recognitions
Pattern Recognition Letters
Comparison of fuzzy numbers using a fuzzy distance measure
Fuzzy Sets and Systems - Fuzzy intervals
Fuzzy Sets and Systems - Special issue: Soft decision analysis
A new measure using intuitionistic fuzzy set theory and its application to edge detection
Applied Soft Computing
Bifuzzy probabilistic sets and r-intuitionistic fuzzy sets
FSKD'09 Proceedings of the 6th international conference on Fuzzy systems and knowledge discovery - Volume 6
A random set description of a possibility measure and its natural extension
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
MPEG VBR video traffic modeling and classification using fuzzy technique
IEEE Transactions on Fuzzy Systems
Fuzzy risk analysis based on similarity measures of generalized fuzzy numbers
IEEE Transactions on Fuzzy Systems
A probabilistic fuzzy logic system for modeling and control
IEEE Transactions on Fuzzy Systems
Unity and diversity of fuzziness-from a probability viewpoint
IEEE Transactions on Fuzzy Systems
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The probabilistic fuzzy set (PFS) is designed for handling the uncertainties with both stochastic and fuzzy nature. In this paper, the concept of the distance between probabilistic fuzzy sets is introduced and its metric definition is conducted, which may be finite or continuous. And some related distances are discussed. The proposed distance considers the random perturbation in progress by introducing the distance of probability distribution, thus it improves the ability to handle random uncertainties, and some inadequacy of the distance of probability distribution is remedied. Finally, a PFS-based distance classifier is proposed to discuss the classification problem, the numerical experiment shows the superiority of this proposed distance in fuzzy and stochastic circumstance.