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Inclusion and similarity measures for interval-valued fuzzy sets based on aggregation and uncertainty assessment
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 …
interval-valued fuzzy sets. We propose a new idea for constructing indicators of inclusion …
Fuzzy and rough approach to the problem of missing data in fall detection system
Two new methods for mining incomplete data based on interval-valued fuzzy set theory and
rough set theory, particularly maximal consistent blocks were proposed, and their …
rough set theory, particularly maximal consistent blocks were proposed, and their …
Early detection of the risk of depressive episodes using a proprietary diagnostic test by new epistemic similarity measures
The first primary motivation of this paper is to propose new methods for measuring similarity
between interval-valued fuzzy sets based on an order relation of the intervals, which are a …
between interval-valued fuzzy sets based on an order relation of the intervals, which are a …
On three types of L-fuzzy β-covering-based rough sets
W Li, B Yang, J Qiao - Fuzzy Sets and Systems, 2023 - Elsevier
In this paper, we mainly establish three types of L-fuzzy β-covering-based rough set models
and study the axiomatic characterizations, matrix representations and interdependency of …
and study the axiomatic characterizations, matrix representations and interdependency of …
[HTML][HTML] Unique Method for Prognosis of Risk of Depressive Episodes Using Novel Measures to Model Uncertainty Under Data Privacy
The research described in this paper focuses on key aspects of learning from data
concerning the symptoms of depression and how to prevent it. The computer support system …
concerning the symptoms of depression and how to prevent it. The computer support system …
Subsethood measure for picture fuzzy sets and its applications on multicriteria decision making
Picture fuzzy set is a direct generalization of intuitionistic fuzzy set and is therefore more
capable of dealing with uncertainty while working on real life problems. The concept of …
capable of dealing with uncertainty while working on real life problems. The concept of …
Federated similarity-based learning with incomplete data
In the analysis of social, medical, and business issues, the problem of incomplete data often
arises. In addition, in situations where privacy policy makes it difficult to share data with …
arises. In addition, in situations where privacy policy makes it difficult to share data with …
Application of entropy measures with uncertainty in classification methods with missing data problem
The problem of measuring the degree of entropy based on precedence indicator and
similarity measures under conditions of uncertainty or imprecision was studied. So we call …
similarity measures under conditions of uncertainty or imprecision was studied. So we call …
Application of similarity measures with uncertainty in classification methods
In this paper, the problem of measuring the degree of inclusion and similarity measure for
interval-valued fuzzy sets is considered. We recall inclusion and similarity measures with …
interval-valued fuzzy sets is considered. We recall inclusion and similarity measures with …
Classification of uncertain data with a selection of relevant features based on similarities measures of Interval-Valued Fuzzy Sets
The article deals with the problem of selecting the most appropriate attributes for a given
classification method with the use of inclusion and similarity measures for interval-valued …
classification method with the use of inclusion and similarity measures for interval-valued …