Fuzzy set theory—and its applications (3rd ed.)
Fuzzy set theory—and its applications (3rd ed.)
On a class of fuzzy c-numbers clustering procedures for fuzzy data
Fuzzy Sets and Systems
Metrics and orders in space of fuzzy numbers
Fuzzy Sets and Systems
Pattern Recognition with Fuzzy Objective Function Algorithms
Pattern Recognition with Fuzzy Objective Function Algorithms
A parametric model for fusing heterogeneous fuzzy data
IEEE Transactions on Fuzzy Systems
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This paper presents fuzzy clustering algorithm for fuzzy data based on α-cuts. A new suitable definition for distance between two arbitrary fuzzy numbers based on α-cuts is proposed. We then reformulate fuzzy c-means FCM with fuzzy data and fuzzy centers based on α-cuts. The effectiveness of the proposed clustering algorithm is tested for three fuzzy data sets and then it is compared with other methods; the fuzzy c-number FCN algorithm, Hathaway's FCM algorithm and the mixed-type variables FCM MVFCM algorithm.