Fuzzy Sets and Systems
Fuzzy sets, uncertainty, and information
Fuzzy sets, uncertainty, and information
Fuzzy set theory—and its applications (3rd ed.)
Fuzzy set theory—and its applications (3rd ed.)
Cluster analysis based in fuzzy relations
Fuzzy Sets and Systems - Special issue on clustering and learning
Pattern Recognition with Fuzzy Objective Function Algorithms
Pattern Recognition with Fuzzy Objective Function Algorithms
Methods and Applications of Interval Analysis (SIAM Studies in Applied and Numerical Mathematics) (Siam Studies in Applied Mathematics, 2.)
Establishing performance evaluation structures by fuzzy relation-based cluster analysis
Computers & Mathematics with Applications
Advances and challenges in interval-valued fuzzy logic
Fuzzy Sets and Systems
Similarity relations and fuzzy orderings
Information Sciences: an International Journal
Optimality test for generalized FCM and its application to parameter selection
IEEE Transactions on Fuzzy Systems
Mathematical and Computer Modelling: An International Journal
A method of relational fuzzy clustering based on producing feature vectors using FastMap
Information Sciences: an International Journal
New similarity measures between interval-valued fuzzy sets
Proceedings of the 15th WSEAS international conference on Systems
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A similarity relation with its partition tree has been applied in the performance evaluation area for obtaining an agglomerative hierarchical clustering. These fuzzy relation-based methods require a decision maker to perform pair-wise comparisons for the similarity among criteria as forming a fuzzy relation matrix. The approach is developed based on real membership values of fuzzy relations. However, interval-valued memberships may be better than real membership values to represent higher-order imprecision and vagueness for human perception. Thus, in this paper we would like to extend fuzzy relations to interval-valued fuzzy relations and then construct interval-valued similarity relations for performance evaluation. We first give some definitions for these interval-valued types of fuzzy relation, similarity relation and resolution form. We then construct an interval-valued fuzzy similarity relation into a hierarchical structure schema. It is shown that both of procedures and results for the partition tree derived from interval-valued and crisp-valued similarity relation matrices have some corresponding relationships and different merits. To demonstrate the usefulness of the proposed approach, performance evaluations for academic departments of higher education are considered by using actual engineering school data in Taiwan.