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Online group streaming feature selection using entropy-based uncertainty measures for fuzzy neighborhood rough sets
Online group streaming feature selection, as an essential online processing method, can deal with dynamic feature selection tasks by considering the...
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Dynamic Feature Selection Based on F-fuzzy Rough Set for Label Distribution Learning
Label distribution learning(LDL) has been received widespread attention as an effective learning paradigm in the field of data mining. However,...
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Rough Fuzzy K-Means Clustering Based on Parametric Decision-Theoretic Shadowed Set with Three-Way Approximation
Rough fuzzy K-means (RFKM) decomposes data into clusters using partial memberships by underlying structure of incomplete information, which...
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Multi-criteria group decision-making for evaluating efficient and smart mobility sharing systems using Pythagorean fuzzy rough numbers
Shared mobility initiatives offer real possibilities to overcome problems such as traffic congestion, air pollution, and natural resource depletion...
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Gallbladder CT Image Segmentation by Integrating Rough Entropy Thresholding with Contours
Jitani, N. Singha, B. Barman, G. Talukdar, A. Choudhury, B. K. Sarmah, R. Bhattacharyya, D. K.Thresholding is one of the most widely used techniques...
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Attribute reduction algorithm of neighborhood rough set based on supervised granulation and its application
In neighborhood rough set theory, attribute reduction based on measure of information has important application significance. The influence of...
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Improved risk assessment model based on rough integrated clouds and ELECTRE-II method: an application to intelligent manufacturing process
Failure Modes and Effect Analysis (FMEA) is a significant mathematical technique for the risk assessment of the failure modes in the industrial...
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Entropy based optimal scale selection and attribute reduction in multi-scale interval-set decision tables
One of the current research gaps in multi-scale data analysis is studying information systems characterized by attributes with interval sets as...
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An incremental approach to feature selection using the weighted dominance-based neighborhood rough sets
Dominance-based neighborhood rough set (DNRS) is capable to give qualitative and quantitative descriptions of the relations between ordered objects....
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Differential evolution-based transfer rough clustering algorithm
Due to well processing the uncertainty in data, rough clustering methods have been successfully applied in many fields. However, when the capacity of...
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Attribute reduction based on interval-set rough sets
As an important extension of the rough set theory, interval-set rough sets provide an effective method to solve the problem that the objective sets...
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Feature gene selection based on fuzzy neighborhood joint entropy
This paper addresses the feature selection problem for gene expression profiles. Feature selection based on fuzzy neighborhood rough sets is very...
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Dual interval rough integrated cloud COPRAS method: a novel hybrid assessment model for remanufacturing system selection
Uncertain and fuzzy linguistic variables are oftenly used to express evaluation information of experts in group decision making approaches. To...
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Mixture Kernel-Based Fuzzy-Rough Feature Selection
Fuzzy-rough sets are a hybridisation of fuzzy sets, which encapsulate the related but distinct concepts of fuzziness and indiscernibility in the case...
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A new rough PROMETHEE approach for the evaluation of potential failure modes and their effects in a general anesthesia process
Failure modes and effects analysis (FMEA) is a systematic framework applied to recognize and eliminate viable failures within objects, services,...
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Feature selection using self-information and entropy-based uncertainty measure for fuzzy neighborhood rough set
Feature selection based on the fuzzy neighborhood rough set model (FNRS) is highly popular in data mining. However, the dependent function of FNRS...
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Decision making model for design concept evaluation based on interval rough integrated cloud VIKOR
Design concept evaluation (DCE) plays a significant role at early design phase of new product development which is processed by experts’ assessments....
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Rough-Fuzzy CPD: a gradual change point detection algorithm
Changepoint detection is the problem of finding abrupt or gradual changes in time series data when the distribution of the time series changes...
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Dynamic graph-based attribute reduction approach with fuzzy rough sets
Incremental datasets are becoming increasingly common as interesting data are continually accumulated across various application fields. Selecting...
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Prediction of the inertial permeability of a 2D single rough fracture based on geometric information
The apparent permeability of a single rough fracture undergoes complex evolution in a non-Darcy flow regime, making description of the nonlinear flow...
