Rough Sets
A Combined Rough Sets–K-means Vector Quantization Model for Arabic Speech Recognizer
... Rough sets approach is a mathematical approach that can be used for attributes reduction and objects classification based on their ...or sets of objects where objects are roughly equal or roughly ...
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A new comprehensive attribute weight algorithm with rough sets theory
... But rough sets theory[1,2] is a valid mathematical theory developed in recent years, which can analyze and deal with imprecise, incomplete and inconsistent information effectively, and can dig out the ...
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Recommendation Method with Rough Sets in Restaurant Point of Sales System
... approach, rough set theory can effec- tively deal with all kinds of inaccurate, inconsistent, and incomplete ...approaches, rough sets have several advantages by easily handling fuzzy ...past, ...
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Port throughput influence factors based on neighborhood rough sets: An exploratory study
... This article aims at reducing attributes for factors of port throughput using the theory of Neighborhood Rough Sets, finding out the key influential factors for port throughput. In order to provide support ...
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Rough Sets Clustering and Markov model for Web Access Prediction
... a rough set clustering to cluster web transactions from web access logs and using Markov model for next access ...a rough sets scheme in which search similarity measure to compute the similarity ...
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On modified soft rough sets on a complete atomic Boolean lattice
... and rough set theory are treated as mathematical approaches to deal with ...soft rough sets. In 2013, we introduced the notion of soft rough sets on a complete atomic Boolean lattice as ...
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Use of Rough Sets Theory in Point Cluster and River Network Selection
... the rough sets to the point cluster and river network ...of rough sets, first, we structuralize and quantify the spatial information of objects by convex hull, triangulated irregular network ...
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System model of college students’ network behavior research based on rough sets
... on rough sets which only achieves a small number of targets for the analysis system of network behavior research and acquires some initial and periodical ...of rough analysis. As an emerging soft ...
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Fuzzy Rough Sets for Self-Labelling: an Exploratory Analysis
... The aim of this contribution is to evaluate the predictive capacity and the stability of a selection of fuzzy rough approximation operators in a semi-supervised setting. Recall that the latter means that some (or ...
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A Comparative Analysis of Rough Sets for Incomplete Information System in Student Dataset
... Abstract— Rough set theory is a mathematical model for dealing with the vague, imprecise, and uncertain knowledge that has been successfully used to handle incomplete information ...of rough set theory, ...
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Feature Subset Selection using Rough Sets for High Dimensional Data
... Mining. Rough Set Theory (RST) is an extension of set theory for study of the intelligent systems characterized by insufficient and incomplete ...approximations. Rough Set Theory (RST) is a good candidate ...
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An Exponential Kernel based Fuzzy Rough Sets Model for Feature Selection
... Fuzzy rough set plays a prominent role in dealing with imprecision and ...fuzzy rough sets with kernel ...fuzzy rough sets approach and an Exponential kernel approximation based fuzzy ...
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Local Search Inspired Rough Sets for Improving Multiobjective Evolutionary Algorithm
... two sets: the nondominated points (NS) and the dominated ones ...two sets we want to create a grid to describe the set NS in order to intensify the search on ...DS sets as in a rough ...
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Applications of Rough Sets Theory in Data Preprocessing for Knowledge Discovery
... Rough sets theory was introduced by ...datasets. Rough sets offer many opportunities for developing many Knowledge Discovery methods using partition properties and discernability matrix [18], ...
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Optimizing Network Routing by Deducing a QoS Metric Using Rough Sets
... The paper proposes a general purpose metric QoSMR, that evaluate the network performance. This metric sorts the best paths regarding the on-line information about network elements. The QoSMR concludes many parameters, ...
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Rough Sets in Imbalanced Data Problem: Improving Re sampling Process
... plying rough sets theory to the imbalanced data learning problem could be a promising research direction, the improved re–sampling approach combining selective preprocessing and editing techniques is ...
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Limits of it -soft sets and their applications for rough sets
... soft sets theory are progressing ...soft sets theory and used this theory to solve some decision making ...soft sets with description ...soft sets, rough sets and fuzzy ...soft ...
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On Links between Rough Sets and Digital Topology
... of rough sets, proposed by Pawlak [1] [2], is an extension of the set theory for the study of intelligent systems characterized by insufficient and incomplete ...the rough set theory, knowledge ...
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Weight selection strategies for ordered weighted average based fuzzy rough sets
... in the literature (e.g. review [18]). Both the traditional model and its later ex- tensions have been used successfully in many different areas of machine learning [37], such as feature selection, instance selection, ...
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T-Rough Sets Based on the Lattices
... between rough sets and algebraic ...to rough sets have been given and studied by Bonikowaski in [6], Iwinski in [14], Rosenfeild in [30] and ...of rough set and rough ...of ...
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