rough set

The core concept of this paper is the theory of Rough Set and Granular Computing, the method of article comparing is researched.

This model reduces attributes by knowledge amount of information for a rough set, and a minimal reduction set is formed.

On the basis of that, redundancy attributes are eliminated using rough set reduction algorithm. Reduction attributes and rules are gained.

The theory of rough-set points out that knowledge has granularity and defines the concept of roughness of knowledge.

In the theory of rough set, attribute reduction of decision table was an important research subject.

Attribute reduction is one of the core issues of the rough set theory and it has become a hot topic of the rough set theory research.

The core of rough set theory is a pair of non-numerical operators, i. e. lower and upper approximation operators.

The discretization of continuous attributes is one of the most main problems in applying of rough set theory.

The Attribute reduction of Information system is one of the focus of Rough Set Theory and Applied research.

The graphic structure analysis for algebraic relationship of rough sets is a new research direction of the rough set theory.

The sorting is one of the most important tasks in the data mining and the decision tree and rough set are two main methods used to sort.

Under incomplete information system, rules extraction is one of the key problems of rough set theory.

the definitions about the upper approximation of the covering rough set are found to be inconsistent.

Fuzzy set theory and rough set theory has a strong complementary in dealing with uncertain problem.

Furthermore, the definition of attribute reduction in generalization rough set and its greedy algorithm were proposed.

Attribute reduction is a rough set approach in data mining that determines the set of important attributes to represent the IS.

The method of it is to apply rough set and neural network to fault diagnosis of aluminium electrolysis.

Attributes reduction is one of important parts researched in rough set theory.

The rough set method was applied to determine the weights of indexes and the objectivity of index weight was achieved.

when we describe the fuzzy concept of approximate space in rough set theory , the fuzzy rough set was generated correspondingly.

Rough set, with its ability in dealing with uncertainty and vagueness, is widely applied in the study of data mining.

At the same time, the weight of each attribute was determined by the dependency degree of rough set applied into optimal selection.

Rough set theory and its application is a new academic focus, widely used in a lot of fields.

The characteristics of Rough set theory and Artificial Neural Network are very bright and obviously complementary.

Rough set theory can remove redundant information in the data to achieve optimal testing points and characteristics of the parameters.

These algorithms are more efficient and effective compared to the traditional methods for operating rough set.

The attribute reduction is one of the cores of Rough Set (RS) theory.

By an example, the advantage and disadvantage of rough set in data processing is analysed in detail.

To avoid the subjectiveness of experts in extracting diagnosis rules, rough set theory is introduced into extracting diagnosis rules.

First, according to reduction theory of rough set, the initial index system can be simplified by deleting the highly related indicators.

In rough set theory, data reduction is a very important issue, it includes attributes and attribute values reduction.

In this thesis for the doctorate, several expanded rough set models are deeply investigated in the incomplete information systems.

For improving, applying rough set theory, analyses the test paper, and discovers both redundance and significant level information.

Soft computing includes Artifical Neural Networks, Fuzzy Logic, Evolutionary Algorithms, Rough Set (RS) Theory, etc.

From the relation, the reduction of attributes for the decision table is conducted by applying the rough set theory to gain decision rules.

The reduction problem of decision table, which is one of Rough Set techniques, is researched. The reduced algorithm was given.

As a new popular theory in the AI field, rough set can effectively express and reduce incomplete and uncertain knowledge.

Comprises useful routines for machine learning in general and for rough set theory in particular.

The user feature extraction algorithmic in this paper reference from attribute reduction and decision rule extraction of rough set theory.

Experiments demonstrate that the method of rough set is efficient for learning classification rules of spatial objects.

The determination of feature core may be significantly contributory to solve the problem of feature reduction in rough set theory.

The made rules are simple and accurate compared with other methods, rough set has several advantages in processing crude information.

Next, the Research of Rough Set Relationship Graphics Representation Knowledge Simplified.

Rough set theory is an useful tool to process inaccurate data, reduction is an important concept in rough set.

We design and implement diagnostic system for rough set theory spleen deficiency syndrome differentiation.

The decision table was established by the rough set theory to make the knowledge reduced and determine the relevant evaluating indexes.

The results of experiments showed that it has a good affection by using rough set.

The concepts of synthesis source and field in synthesis reasoning were introduced into decision systems in rough set theory.

Discretization of continuous attributes is the key step in processing continuous problem with rough set theory.

There are many close relations between the genetic characteristics of S-rough set and the genetic characteristics of metal.

The results show that the online simple fault diagnosis based on rough set is realized and the system resource of sub-node is saved.

Firstly, customer demand and production index of make-to-order company were proposed and simplified with rough set theory.

Attribute reduction, a basic conception in rough set theory, is introduced at first, then applied to forestry information management.

To solve the problem of conflict resolution case reasoning in collaborative design, a rough set-based case reasoning strategy was presented.

Rough set theory, a new effectiveness evaluation theory, is used to evaluate the effectiveness of satellite navigation systems.

Furthermore, data mining technologies based on rough set are applied to the tax warehouse to improve the efficiency of tax inspection.

All of these have shown how to make use of the Rough Set theory to make valuable information for the management decision in the enterprise.

This algorithm used powerful attribute reduction and rule making ability of the rough set.

Last, the Research of Rough Set Relationship Graphics Representation Knowledge Base.

In this paper, the authors present a method combined rough set ( RS ) with least square support vector regression (LS-SVR).

Rough set theory is a new mathematical analysis method processing fuzzy and uncertainty knowledge.

Methods: Rough set was used as data mining tool for extracting the potential diagnostic rules of TCM gastropathy.

It preprocesses the training set by using neighborhood rough set model to delete those abnormal samples and disturbances.

In this paper, we discussed the character of rough set and put forward the application model of rough set in data processing.

This paper proposes a new rough set-based heuristic function called weighted average support heuristic.

Rough set is another tool which is dealing ambiguous and uncertain problems after theory of probability, fuzzy set and evidence theory.

Introduct the classical rough set theory and the rough set attribute reduction method is applied to the study of feature selection.

Attribute reduction in rough set theory is a NP-hard problem, which is studied mainly to design a more efficient algorithm.

A model was built for a team's capabilities based on rough set theory, and the experience of former evaluations was summarized.

The possibility of the integration of rough set method and neural network based theshortage of BP network is discussed.

An example was trained and actually diagnosed with the hybrid system of rough set-neural network-expert system on this platform.

Rough set theory is a new mathematical means to deal with vagueness and uncertainty.

A novel rough set-based method followed by establishing a mix discernibility matrix is introduced for intrusion detection, and choose C4.

The reliability of the axiom group, which shows that characterizing of rough set theory based on similar relation is rational, is proved.

A new automatic recognition system of bills is designed on the basis of the principal curves and rough set methods.

The famous rough set is useful tool to solve the problem of ambiguity, complexity, random city and less distinguish ability.

A method that uses rough set for the learning of classification rules about 2-dimensional spatial objects was presented.

This paper improves the Pawlak Rough Set Model based decision tree inducing approach according to the Variable Precision Rough Set Model.

Rough set theory is a new data computing tool to deal with vagueness and uncertainty.

Rough Set theory is a new mathematic tool to deal with fuzzy and uncertain knowledge.

For a complicated discrimination of air pollution, a new model of BP Networks is proposed based on Rough Set.

Secondly, we make use of rough set to give synthesizing evaluation score to every object through the dispersed data.

Further expand the application of the variable precision rough set in the financial analysis, have some innovative and practical.

This paper proposes a rough set-based method of abstracting rules, and validates it with an example.

According to fuzzy rough set theory, a comprehensive data mining method is proposed and applied in spatial load forecasting (SLF).

Then data reduction in rough set theory based on difference-identity relation is discussed. Further displays the essence of reduction.

A new approach employing rough set theory and Fourier-Mellin transform to solve HRRP recognition problem is presented here.

Thirdly, the bridge maintenance chaning management decision on improved rough set was proposed.

The research of exact and effective data reduction algorithms based on Rough Set has greatly theoretical value and realistic meaning.

Aiming at incomplete information of indicator system, this paper sets up null value dealing model of indicator system based on rough set.

Based on the attribute reduction of rough set, from different aspects, this paper sets up indicator screening model based on rough set.

For generalizing the content of synthesis reasoning, the model of synthesis reasoning based on rough set theory was proposed.

Absrtact: Rough set theory is a new mathematical tool to research imprecise and uncertain knowledge.

Rough set theory has the advantage of data reduction and rule extraction, and can initialize the structure of network.

The attributes reduction of Rough Set is NP problem, and it makes Rough Set hard to use broadly in reality.

A novel method that makes use of rough set theory to detect moving small target with low SNR in infrared image sequences is presented.

The main results obtained are as follows: 1. based on the classical theory of rough set attribute reduction feature selection methods.

Rough set theory is a new math tool in dealing with fuzzy and uncertain knowledge.

Finally, based on the above escaping model combine the Rough Set theory with Cellular Automata to state the cells evolution.

This paper aims to explore the critical patterns between KM and corporate performances by using the rough set approach.

Relevance feedback algorithm based on support vector machine and rough set for image retrieval is approached.

To the dynamic traits of group formation in situation assessment, the methods based on S-rough set theory are studied.

To the dynastic demands in-group formation in situation assessment, a method based on S-rough set theory is put forward.

Combined rough set theory and gray theory, and studied interval gray information system based on dominance relation.

To characterize similar rough set theory, an axiom group named S, consisting of 3 axioms, is proposed.

Among so many methods, Rough Set Theory is a kind of more valid method to deal with the complicated systems.

In addition, the author incorporated Variable Precision Rough Set (VPRS) model to effectively control information loss.

Weighted rough set (WRS) model is an extension of rough set (RS), based on variable precision rough set (VPRS) model.

Of all the numerous data processing methods, Rough Set Theory is a solution that can play a large role in image processing.

A new method for filtering of X - ray digital image of chest based on multi - resolution and rough set was developed in this paper.

Then discusses the attributes reduction based on Rough Set theory and set covering problem to combine them.

A novel artificial network model based on fuzzy-rough set for gas emission forecasting of coal is proposed in the paper.

This paper research a data mining system based on incremental updating algorithms of rough set theory.

combines rough set with fuzzy set, and sets up comprehensive evaluation method based on rough set and fuzzy set.

The combined use of rough set theory arid group eigenvalue method in the renew able evaluation of water resources is feasible.

Reduction of knowledge is the core of rough set theory .

This paper researches a data mining system based on attributes reduction of rough set theory.

To show the application of the rough set theory, a rough set approach based on random sets is proposed.

In view of the charateristics and types of the turntable's fault, a fault diagnosis system based on neighborhood rough set is designed.

Based on rough set theory, a new fault diagnosis method of power electronic circuits was presented.

Aim To establish a generalized model of rough set theory based on quasi order relation.

In addition, we combined SVM with rough set theory, and got rough support vector machine algorithm (RSVM).

The three main steps during data mining based on rough set are data preparation, reduction, and generating rules.

So a new Bayesian model mixed tree augmented Naive Bayes classifier(MTANC) based on the rough set theory is presented.

A method of compressor fault diagnosis based on rough set theory is proposed.

In order to overcome the limitation of the method, an improved fault line detection method based on rough set theory is presented.

The new rough entropy can measure not only the size of uncertainty region in rough set but also the partition granularity.

Rough set method is used in the study of optimum population city.

The third, a credit risk assessment model is designed and implemented based on rough set theory.

A case retrieval method was presented based on rough set theory in order to solve the retrieval problem in design of stamping dies.

In order to get the reduction of attribute, the paper proposes a rough set attribute reduction algorithm based on AGA .

And based on DLS, we introduce the method of RSDA (Rough set and data analysis), which is a technique of data mining.

Instead the researcher put forward many kinds of generalized rough set models in order to expand its applications areas.

In this dissertation, we try to study the organic combination of the t-norm operator set, rough set and fuzzy set.

Rough set is a mathematical approach to study imprecise, uncertain or incomplete information or knowledge.

Updating Approximate Concept of Rough Set Resulting from Inserting or Deleting Attributes in Incomplete Information System

Attribute Reduction of a Rough Set and Its Application in Forestry Information Analysis

Variable Precision Rough Set Model and a Knowledge Reduction Algorithm for Incomplete Information System

On extension model of rough set of incomplete information systems under symmetric similarity relation

Rough-Set-Based Spatiotemporal Assignment Mining Model with Its Application for Marine Fishery

Enterprise Resources; Strategic Resources; Resource Structure; Rough Set; Structural Equation;

Studying Direction of Granular Computing from Rough Set Perspective of Development

Extension of Rough Set Methodology for Probabilistic Decision Analysis from Preferential Multiple Attribute Decision Tables

The Extension of the Indiscernibility Relation of Rough Set and Its Visualization

Rough set theory and application of it in fault diagnosis

Mining Quantitative Association Rules in Rough Set and A Method of Rules Reduction

Then, on the basis of the content above, explores and demonstrates the feasibility of the fusion of rough set and neural networks;

An Approach to Determine Rules and Formula of Ore Grade Estimation Using Variable Precision Rough Set Theory

Application of a rough-set neural network to superfamily level in insect taxonomy

Rough Set CMAC Neural Network and Its Application in Nonlinear System Identification

The Research on Rough Set Theory-based Determining Weight Coefficients of Distributors'Performance Evaluation

Variable Set-Pair Connectivity Extension of Rough Set Model and its Attributes Reduction

Rough Set-based Classification and Attribute Reduction Under Incomplete Information Systems

The evaluation model for relative competition power of carmanufacturing enterprises based on Rough Set theory and its applications

The Calculating Method in Rough Set by Translating Decision Tables and Its Application

Research and Application on Rough Set of Intelligent Maintenance DSS

An extended rough set methodology for probability decision analysis with incomplete information

Data Mining; Clustering Analysis; Outlier Detection; Rough Set Theory; Genetic Algorithm;

Approach to Information Getting Rough Set of Economic Early Warning

Study of a Heuristic Rule Reduction Algorithm Based on Rough Set and Fuzzy Set

Document classification approach by rough-set-based corner classification neural network

Research on Rough-set-based Knowledge Acquisition in Power System Electric Network Fault Diagnostic Expert System

Application of the Rough Set Theory in the Evaluation of the Public Servants Quality in Rural

Algorithm of rough set attributes reduction integrated with the consistency criterion

Comparison of the Reliability between Rough Set Decision Table and Reduction of Decision Table

Expression in rough set for logic function and a method of minimization

Study on Solving Algorithms of Compatible Classes of Rough Set with Maximal Compatible Classes as Primitive Granules

Rough Set-based Knowledge Acquisition Methodology in Virtual Assembly Environment

Variable Rough Set Model and Its Properties for Incomplete Information System

analysis and comparative of rough - set theory and principal components analysis to double allele frequency

Rough Set Criterion of Significance of Influence Factors to Cutting Characteristic Functions

Study of weighted D-S evidence combination based on rough set theory and its application

Study of multi-objective optimization problem based on the rough set attribute reduction methodology

An improved CART algorithm involving Rough Set theory and its application

Rough Set; Granular Computing; Tolerance Granule; Article Comparing;

Rough Set Theory Used for Data Mining

Rough Set-Neural Network and its Application to Cation Anti-flotation Control

Application of the Variable Precision Rough Set Model in Decision Tree Construction

A Rough Set Based Comprehensive Evaluation Decision MODEL of Combat Aircraft Program Engineering

Study on the Application of Rough Set Theory in Substrate Feeding Control and Fault Diagnosis in Fermentation Process

Clustering of Rough Set of Qualitative Data of High Dimension in Data Mining

The Application of a New Rough Set Approach to Non-complete Information System

Rough set based multi-agent system cooperation for industrial supervisory interface system

Approximate Decision Rules and Matching Rules in Rough Set Based Classification Algorithms

Application of Rough Set Theory in Target Identification Information Processing

Fault Diagnosis Model for the Regenerative Heating System of a Steam Turbine Unit Based on a Rough Set Theory

A Knowledge Acquisition by Rough Set Based on Incomplete Data Sets and Its Application in Fault Diagnosis for Electricity Networks

Sensitivity Analysis of Quantifying Algorithm for Continuous Attributes of Rough Set

The Application of Rough Set for High-tech District Second Development Economic Strength Evaluation

The Application Study of Rough Set Theory in Power System Data Mining

Information Representation for Attribute Reduction of Decision Tables in Rough Set Theory

grid enterprise; risk management; risk element; the risk element transmission; rough set;

Extension of the concept of rough set based on equivalence operator in pansystems

Database decomposition approach with rough set based feature selection measure

Rough set theory and its application in fault diagnosis technology

The rough set theory applied in the random statistic strength analysis of the automobile frame

Rough Set-based Attribute Reduction under Incomplete Information Systems

Rough Set Theory and Its Application in Fault Diagnosis in Nuclear Power Plant

Rough Set Theory and its Application to Intelligent Reasoning

An Information Representation of the Concepts and Operations in Rough Set Theory

Reliability analysis to deal with imperfect information by rough set theory

Hybrid System of Rough Set - Neural Networks - Expert System and Its Applications

Wavelet packet and rough set based approach for fault diagnosis of reciprocating compressors

Rough Set Model and Precision Reduction in Incomplete and Fuzzy Decision Information Systems

Application of Rough Set-based Evolutionary Computation to Smith Control of Time-Delay System

Research on application of rough set decision tree algorithm in hospital infection diagnosis

Generalized discretization of continuous attributes in rough set theory

Rough set theory and its application in cation anti-flotation control

Brief introduction and applying potential analysis of rough set theory in the electric power station field

Application of rough set fuzzy neural network method on criterion of characteristic of coal ash slagging

Rough set theory and its application in geologic graphics system

Applications of Rough Set Approach in the Fusion of Communication Intercept Information

Improvement of Definitions of Rough Function and Proof of Rough Derivative's Properties in Rough Set Theory

Rules Mining of the University Teacher's Performance Appraisal System on Rough Set

Fineness and coarseness of an approximation space in the rough set theory

RBF Artificial Neural Network Based on Rough Set and Its Application in Equipment Development Cost Estimation

Application of Rough Set Theory to Comprehensive Evaluation of Working Quality of Hospital

The Greedy-Rough Set Attribute-Reducing Algorithms of Classification Mining

Rough Set-based Weighted Decision Algorithm for Database Information Mining

A Survey on Rough Set Theory and Its Application on Intelligent Control

The Application of Rough-set Based Clustering Algorithm in Intrusion Detection System

Rough Set Theory and Its Application in Short-term Load Forecasting

Application of Rough Set Theory to the Identification of Fuzzy Membership Function

Approximation optimality for evolutionary rough set

Lower and upper approximation of rough set, boundary region and rough membership function

Application of rough set neural network system in fighter plane structure fault diagnosis

Rough set theory and knowledge quantity use in the system of monitor on wind machine

Rough set theory and its application in the intelligent systems

Rough Set Based Missing Data Rotative Reconstruction Algorithms

Rough set-based conflict resolution case reasoning in collaborative design

Rough Set Approach to Partnership Selection in Formation of Virtual Enterprises

Application Research on Rough Set Theory in Process Quality Control of Aviation Products

Rough set method for invalid and absent signal treatment in power station fault diagnosis system

A Rough Set-Based Method for Constructing Simple Bayesian Classifier from Databases

Application of Rough Set Theory in Knowledge Mining of Underground Mine Dispatching

Analysis of Students'Interest of Computer Operating Course through Rough Set Theory

The Application of Rough Set Theory in Attributes Reduction and Knowledge Partition

Knowledge Reduction Analysis of User Satisfaction Survey with Rough Set Theory

An Incremental Learning Approach for Rough Set Neural Network Monitoring Model

Application research of rough set theory in wastewater parameters soft measure

A Comparative Study between the Reduction of Knowledge Based on Rough Set Theory and the Statistical Classification

Research on Rough Set Theory and Its Progress on Applications

Applications of Rough Set Theory in the Recognition of Communication Station's Platforms

Study on the Method of Knowledge Reducing and Decision Reasoning for Rough Set in incomplete Information System

Rough Set Application in Forestry Information Management

On applications of rough set and artificial neural networks in tax revenue early-warning system

Attributes Reduction and Structured Selection in Automatic Cartographical Generalization Based on Rough Set

Attribute Reduction Using Attribute Variable Partition of Rough Set

Research and Application of a CRM-Oriented Incremental Algorithm Based on the Rough Set

Knowledge Inclusion Degree and Information Entropy of Rough Set Data Analysis