56,043 research outputs found
Extending Similarity Measures of Interval Type-2 Fuzzy Sets to General Type-2 Fuzzy Sets
Similarity measures provide one of the core tools that enable reasoning about
fuzzy sets. While many types of similarity measures exist for type-1 and
interval type-2 fuzzy sets, there are very few similarity measures that enable
the comparison of general type-2 fuzzy sets. In this paper, we introduce a
general method for extending existing interval type-2 similarity measures to
similarity measures for general type-2 fuzzy sets. Specifically, we show how
similarity measures for interval type-2 fuzzy sets can be employed in
conjunction with the zSlices based general type-2 representation for fuzzy sets
to provide measures of similarity which preserve all the common properties
(i.e. reflexivity, symmetry, transitivity and overlapping) of the original
interval type-2 similarity measure. We demonstrate examples of such extended
fuzzy measures and provide comparisons between (different types of) interval
and general type-2 fuzzy measures.Comment: International Conference on Fuzzy Systems 2013 (Fuzz-IEEE 2013
Triangular norms which are join-morphisms in 3-dimensional fuzzy set theory
The n-dimensional fuzzy sets have been introduced as a generalization of interval-valued fuzzy sets, Atanassov's intuitionistic and interval-valued intuitionistic fuzzy sets. In this paper we investigate t-norms on 3-dimensional sets which are join-morphisms. Under some additional conditions we show that they can be represented using a representation which generalizes a similar representation for t-norms in interval-valued fuzzy set theory
A New Penta-valued Logic Based Knowledge Representation
In this paper a knowledge representation model are proposed, FP5, which
combine the ideas from fuzzy sets and penta-valued logic. FP5 represents
imprecise properties whose accomplished degree is undefined, contradictory or
indeterminate for some objects. Basic operations of conjunction, disjunction
and negation are introduced. Relations to other representation models like
fuzzy sets, intuitionistic, paraconsistent and bipolar fuzzy sets are
discussed.Comment: The 12th International Conference Information Processing and
Management of Uncertainty in Knowledge-Based Systems, June 22-27, 2008,
Malaga, Spai
Hierarchical fuzzy logic based approach for object tracking
In this paper a novel tracking approach based on fuzzy concepts is introduced. A methodology for both single and multiple object tracking is presented. The aim of this methodology is to use these concepts as a tool to, while maintaining the needed accuracy, reduce the complexity usually involved in object tracking problems. Several dynamic fuzzy sets are constructed according to both kinematic and non-kinematic properties that distinguish the object to be tracked. Meanwhile kinematic related fuzzy sets model the object's motion pattern, the non-kinematic fuzzy sets model the object's appearance. The tracking task is performed through the fusion of these fuzzy models by means of an inference engine. This way, object detection and matching steps are performed exclusively using inference rules on fuzzy sets. In the multiple object methodology, each object is associated with a confidence degree and a hierarchical implementation is performed based on that confidence degree.info:eu-repo/semantics/publishedVersio
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