New covering techniques and applications utilizing multigranulation fuzzy rough sets
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DOI: 10.1007/s10462-024-10860-w
Abstract: In order to conduct an in-depth study of Zhan’s methodology pertaining to the covering of multigranulation fuzzy rough sets (CMG\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\hbox {C}_{{MG}}$$\end{document}FRSs), we build two families: the… read more here.
Keywords: multigranulation fuzzy; rough sets; documentclass 12pt; document ... See more keywords
The Application of Rough Sets Theory to Design of Weld Defect Classifiers
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DOI: 10.1007/s10921-017-0420-x
Abstract: The innovative method for weld defect classification based on rough set theory is presented in this study. The classification rules have been generated by processing of data base composed of 640 radiographic images referring to… read more here.
Keywords: sets theory; design weld; theory design; application rough ... See more keywords
Closed-set lattice and modular matroid induced by covering-based rough sets
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DOI: 10.1007/s13042-014-0314-5
Abstract: Covering is a common form of data representation, and covering-based rough sets, a technique of granular computing, provide an effective tool to deal with this type of data. However, many important problems of covering-based rough… read more here.
Keywords: closed set; types matroids; covering based; based rough ... See more keywords
New types of soft rough sets in groups based on normal soft groups
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DOI: 10.1007/s40314-020-1098-8
Abstract: Hybridization of soft sets and rough sets is an important way to deal with uncertainties. This paper aims to study the concept of roughness in soft sets over groups. In this regard, a pair of… read more here.
Keywords: sets groups; approximation spaces; normal soft; rough sets ... See more keywords
A Novel Approach to Decision Analysis Using Dominance-Based Soft Rough Sets
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DOI: 10.1007/s40815-019-00612-2
Abstract: A number of useful mathematical tools such as fuzzy sets, rough sets and soft sets have been developed to deal with problems involving various uncertainties. These theories have been found to be particularly useful in… read more here.
Keywords: analysis; rough sets; approach; based soft ... See more keywords
Axiomatic characterizations of L-fuzzy rough sets by L-fuzzy unions and L-fuzzy intersections
Sign Up to like & getrecommendations! Published in 2022 at "International Journal of General Systems"
DOI: 10.1080/03081079.2021.2024178
Abstract: In this paper, considering L being a complete residuated lattice, we first introduce the concept of mediate L-fuzzy relations and give its characterizations by L-fuzzy upper and lower rough approximation operators. Then we provide an… read more here.
Keywords: characterizations fuzzy; rough sets; unions fuzzy; sets fuzzy ... See more keywords
Granular knowledge and rational approximation in general rough sets – I
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DOI: 10.1080/11663081.2024.2336387
Abstract: Rough sets are used in numerous knowledge representation contexts and are then empowered with varied ontologies. These may be intrinsically associated with ideas of rationality under certain conditions. In recent papers, specific granular generalisations of… read more here.
Keywords: granular knowledge; rough sets; rationality; general rough ... See more keywords
RST-DE: Rough Sets-Based New Differential Evolution Algorithm for Scalable Big Data Feature Selection in Distributed Computing Platforms
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DOI: 10.1089/big.2021.0267
Abstract: In data analysis, data scientists usually focus on the size of data instead of features selection. Owing to the extreme growth of internet resources data are growing exponentially with more features, which leads to big… read more here.
Keywords: rough sets; big data; feature; differential evolution ... See more keywords
Deep learning architecture using rough sets and rough neural networks
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DOI: 10.1108/k-09-2016-0228
Abstract: This paper aims to utilize machine learning and soft computing to propose a new method of rough sets using deep learning architecture for many real-world applications.,The objective of this work is to propose a model… read more here.
Keywords: decision; deep learning; learning architecture; rough sets ... See more keywords
A Comparison of Promethee and TOPSIS Techniques based on Bipolar soft Covering based rough sets
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DOI: 10.1109/access.2022.3161470
Abstract: The uncertainty in the data is an obstacle in decision-making problems. In order to solve problems with a variety of uncertainties a number of useful mathematical approaches together with fuzzy sets, rough sets, soft sets,… read more here.
Keywords: rough sets; covering based; decision making; bipolar soft ... See more keywords
A Spectral Feature Selection Approach With Kernelized Fuzzy Rough Sets
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DOI: 10.1109/tfuzz.2021.3096212
Abstract: Feature evaluation is an important issue in constructing a feature selection algorithm in kernelized fuzzy rough sets, which has been proven to be an effective approach to deal with nonlinear classification tasks and uncertainty in… read more here.
Keywords: rough sets; feature; feature selection; kernelized fuzzy ... See more keywords