Results 31 to 40 of about 50,721 (156)
Two kinds of average approximation accuracy
CAAI Transactions on Intelligence TechnologyRough set theory places great importance on approximation accuracy, which is used to gauge how well a rough set model describes a target concept. However, traditional approximation accuracy has limitations since it varies with changes in the target ...
Qingzhao Kong +3 more
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Multigranulation rough set: A multiset based strategy
International Journal of Computational Intelligence Systems, 2017 A simple multigranulation rough set approach is to approximate the target through a family of binary relations. Optimistic and pessimistic multigranulation rough sets are two typical examples of such approach.
Xibei Yang +5 more
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Covering-Based Rough Single Valued Neutrosophic Sets [PDF]
Neutrosophic Sets and Systems, 2017 Rough sets theory is a powerful tool to deal with uncertainty and incompleteness of knowledge in information systems. Wang et al. proposed single valued neutrosophic sets as an extension of intuitionistic fuzzy sets to deal with real-world problems.
Yingcang Ma, Wanying Zhou, Qing Wan
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Fuzzy Rough Sets versus Rough Fuzzy Sets
, 1998 Reihe Computational Intelligence ...
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International Journal of Computational Intelligence SystemsWith advanced technology in medicine and biology, data sets containing information could be huge and complex that sometimes are difficult to handle. Dynamic computing is an efficient approach to solve some problems. Since multigranulation rough sets were
Peiqiu Yu +3 more
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Single Valued Neutrosophic Soft Approach to Rough Sets, Theory and Application [PDF]
Neutrosophic Sets and Systems, 2018 This paper aims to introduce a single valued neutrosophic soft approach to rough sets based on neutrosophic right minimal structure. Some of its properties are deduced and proved. A comparison between traditional rough model and suggested model, by using
Emad Marei
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Equivalent Characterizations of Some Graph Problems by Covering-Based Rough Sets
Journal of Applied Mathematics, 2013 Covering is a widely used form of data structures. Covering-based rough set theory provides a systematic approach to this data. In this paper, graphs are connected with covering-based rough sets.
Shiping Wang +3 more
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Granule Vectors and Granular Convolutional Classifiers
IEEE Access, 2020 Convolutional operations can extract effective features and have been widely used in the field of deep learning. For the deficiency of convolution mainly dealing with numerical data, we propose a novel convolutional operator on granules with a set form ...
Yumin Chen +3 more
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Multi-Attribute Decision-Making Method Based on Neutrosophic Soft Rough Information
Axioms, 2018 Soft sets (SSs), neutrosophic sets (NSs), and rough sets (RSs) are different mathematical models for handling uncertainties, but they are mutually related.
Muhammad Akram +2 more
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The Parameter Reduction of Fuzzy Soft Sets Based on Soft Fuzzy Rough Sets
Advances in Fuzzy Systems, 2013 Fuzzy set theory, rough set theory, and soft set theory are three effective mathematical tools for dealing with uncertainties and have many wide applications both in theory and practise. Meng et al.
Zhiming Zhang
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