Results 31 to 40 of about 3,651 (294)
Adapting fuzzy rough sets for classification with missing values [PDF]
, 2021 We propose an adaptation of fuzzy rough sets to model concepts in datasets with missing values. Upper and lower approximations are replaced by interval-valued fuzzy sets that express the uncertainty caused by incomplete information.
Peralta, Daniel +2 more
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A New Single-Valued Neutrosophic Rough Sets and Related Topology
Journal of Mathematics, 2021 (Fuzzy) rough sets are closely related to (fuzzy) topologies. Neutrosophic rough sets and neutrosophic topologies are extensions of (fuzzy) rough sets and (fuzzy) topologies, respectively. In this paper, a new type of neutrosophic rough sets is presented,
Qiu Jin +3 more
doaj +1 more source
Advances in fuzzy sets and rough sets
International Journal of Approximate Reasoning, 2006 n ...
Masulli, F., Petrosino, A.
openaire +2 more sources
A Hesitant Soft Fuzzy Rough Set and its Applications
IEEE Access, 2019 The difficulty of establishing a common membership degree is not because there is a margin of error or some possibility distribution values, but because there is a set of possible values.
Ting Xie, Zengtai Gong
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On the measurement of TL - fuzzy rough sets [PDF]
, 2006 In fuzzy rough sets a fuzzy T-similarity relation is employed to describe the degree of similarity between two objects and to construct lower and upper approximations for arbitrary fuzzy sets.
Tsang, ECC +3 more
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Rule induction based on fuzzy rough sets [PDF]
, 2007 In this paper, we propose one method of rule induction based on fuzzy rough set. First, the consistence degree is proposed as the basic concept to induce rules based on fuzzy rough sets.
Tsang, ECC +5 more
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IEEE Access, 2023 In recent days, due to the complexities of different diseases of similar types, it becomes very difficult to diagnose an accurate type of disease, and so medical diagnosis becomes a difficult task for the experts working in health departments.
Tahir Mahmood +3 more
doaj +1 more source
Boundary-wise loss for medical image segmentation based on fuzzy rough sets [PDF]
The loss function plays an important role in deep learning models as it determines the model convergence behavior and performance. In semantic segmentation, many methods utilize pixel-wise (e.g. cross-entropy) and region-wise (e.g.
Chen, Xin +3 more
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Certain Types of Covering-Based Multigranulation (ℐ,T)-Fuzzy Rough Sets with Application to Decision-Making [PDF]
, 2020 As a generalization of Zhan’s method (i.e., to increase the lower approximation and decrease the upper approximation), the present paper aims to define the family of complementary fuzzy β-neighborhoods and thus three kinds of covering-based ...
Mohammed Atef +3 more
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Granular Structure of Type-2 Fuzzy Rough Sets over Two Universes [PDF]
, 2017 Granular structure plays a very important role in the model construction, theoretical analysis and algorithm design of a granular computing method. The granular structures of classical rough sets and fuzzy rough sets have been proven to be clear.
Yan-Hui Zhai +3 more
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