JOURNAL ARTICLE
Measures of uncertainty for type-2 fuzzy sets
Abstract
The Extension Principle based on alpha-cuts plays a pivotal role in many applications of type-1 fuzzy sets. We recently defined an alpha-based extension principle for type-2 fuzzy sets. In this paper we investigate the use of the alpha-extension principle to define uncertainty measures for type-2 fuzzy sets. We investigate cardinality, similarity, and subsethood for type-2 fuzzy sets and demonstrate when the alpha-plane representation can be used.
Keywords:
Extension (predicate logic) Type-2 fuzzy sets and systems Fuzzy set Mathematics Alpha (finance) Fuzzy logic Fuzzy number Defuzzification Type (biology) Fuzzy set operations Fuzzy classification Cardinality (data modeling) Artificial intelligence Algorithm Computer science Data mining Statistics
Metrics
16
Cited By
1.20
FWCI (Field Weighted Citation Impact)
34
Refs
0.83
Citation Normalized Percentile
Is in top 1%
Is in top 10%
Citation History
Topics
Fuzzy Logic and Control Systems
Physical Sciences → Computer Science → Artificial Intelligence
Multi-Criteria Decision Making
Social Sciences → Decision Sciences → Management Science and Operations Research
Rough Sets and Fuzzy Logic
Physical Sciences → Computer Science → Computational Theory and Mathematics
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