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Quasi-atomic relations based rough set model and convex geometry
Numerous studies have extensively examined the correlation between convex structures and covering rough set models. However, limited attention has...
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Neighborhood rough set with neighborhood equivalence relation for feature selection
Feature selection of the neighborhood rough set is an important step in preprocessing the data and improving classification performance. Neighborhood...
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Rough set approximations based on a matroidal structure over three sets
Pawlak’s classical model of rough set approximations provides an efficient tool for extracting information exactly by employing available knowledge...
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An incremental approach to hierarchical feature selection by applying fuzzy rough set technique
In the age of big data, the number of class labels is increasing rapidly and there exists a hierarchical structure between different class labels. In...
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Feature selection based on multi-perspective entropy of mixing uncertainty measure in variable-granularity rough set
Neighborhood rough set is an important model in feature selection. However, it only determines the granularity of the neighborhood from a feature...
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A novel approach based on rough set theory for analyzing information disorder
The paper presents and evaluates an approach based on Rough Set Theory, and some variants and extensions of this theory, to analyze phenomena related...
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Feature selection using relative dependency complement mutual information in fitting fuzzy rough set model
As a reliable and valid tool for analyzing uncertain information, fuzzy rough set theory has attracted widespread concern in feature selection....
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Probability rough set and portfolio optimization integrated three-way predication decisions approach to stock price
In the stock market, accurate trend judgment and reasonable asset distribution are effective ways to obtain ideal return. However, the real stock...
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Rough Cuckoo Search: A Novel Mathematics Based Optimization Approach Based on Rough Set
AbstractCuckoo Search Algorithm (CSA) is a robust, flexible, and easily implementable Nature-inspired Optimization Algorithm (NIOA) with fewer...
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A nonadditive rough set model for long-term clinical efficacy evaluation of chronic diseases in real-world settings
The pursuit of clinical effectiveness in real-world settings is at the core of clinical practice progression. In this study, we address a long-term...
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Data classification using rough set and bioinspired computing in healthcare applications - an extensive review
The change in living standard made people to think on their physical health. Accordingly, healthcare organizations are concentrating more on physical...
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The variable precision fuzzy rough set based on overlap and grou** functions with double weight method to MADM
Variable precision fuzzy rough set (VPFRS) is widely utilized for handling various forms of uncertain information due to its fault-tolerant...
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A local multi-granularity fuzzy rough set method for multi-attribute decision making based on MOSSO-LSTM and its application in stock market
Multi-attribute decision-making, based on historical data of attributes, considers multiple attributes and strives to find the optimal solution among...
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A novel rough set-based approach for minimum vertex cover of hypergraphs
Minimum vertex covering has been widely used and studied as a general optimization problem. We focus on one of its variation: minimum vertex cover of...
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FPGA supported rough set reduct calculation for big datasets
The rough sets theory developed by Prof. Z. Pawlak is one of the tools used in intelligent systems for data analysis and processing. In modern...
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A multigranulation rough set model based on variable precision neighborhood and its applications
As combinations of neighborhood rough sets and multigranulation rough sets (MRSs), optimistic and pessimistic neighborhood MRSs can handle complex...
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Uncertainty optimization based feature subset selection model using rough set and uncertainty theory
The rough set is a tool for the assessment of uncertainty, and the rough set reducts formation is the technique to remove uncertainty in the feature...
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Dynamic updating approximations of local generalized multigranulation neighborhood rough set
The approximation space in rough set theory is important for dealing with uncertainties. As the information contained in various information systems...
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Detection of Drug Abuse Using Rough Set and Neural Network-Based Elevated Mathematical Predictive Modelling
In the smart world scenario, the application of the Internet of Things is manifold as its utilization can be observed in health care services, home,...
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Hybridization of rough set–wrapper method with regularized combinational LSTM for seasonal air quality index prediction
In order to survive, mankind needs air. The quality of life depends on the purity of the air we breathe in. Hazardous pollutants are stirred up in...
