Journal
INFORMATION SCIENCES
Volume 547, Issue -, Pages 1182-1200Publisher
ELSEVIER SCIENCE INC
DOI: 10.1016/j.ins.2020.09.072
Keywords
Subsethood; Inclusion; Precedence; Similarity; Interval-valued fuzzy set; Interval-valued aggregation function
Categories
Funding
- Centre for Innovation and Transfer of Natural Sciences and Engineering Knowledge of University of Rzeszow, Poland [RPPK.01.03.00-18-001/10]
Ask authors/readers for more resources
The study focuses on measuring the degree of inclusion and similarity between interval-valued fuzzy sets and introduces a new approach for constructing indicators based on precedence relation, aggregation, and uncertainty assessment. Selected properties and interactions of the proposed measures are examined, followed by a discussion and comparison with existing similarity measures in the literature.
We consider the problem of measuring the degree of inclusion and similarity between interval-valued fuzzy sets. We propose a new idea for constructing indicators of inclusion and similarity measures based on the precedence relation, aggregation and uncertainty assessment. Furthermore, we examine selected properties of the suggested measures and their interactions. Finally, we discuss several similarity measures that appear in the literature and compare them with our novel approach. (C) 2020 Elsevier Inc. All rights reserved.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available