A variable precision rough set model based on the granularity of tolerance relation

2016 ◽  
Vol 102 ◽  
pp. 103-115 ◽  
Author(s):  
Xiangping Kang ◽  
Duoqian Miao
Keyword(s):  
Rough Set ◽  
Tolerance Relation ◽  
Variable Precision ◽  
Model Based ◽  
Variable Precision Rough Set

Variable Precision Rough Set Model Based on Covering Relation and Uncertainty Measure

2013 ◽  
Vol 694-697 ◽  
pp. 2856-2859
Author(s):  
Mei Yun Wang ◽  
Chao Wang ◽  
Da Zeng Tian
Keyword(s):  
Rough Set ◽  
Uncertainty Measure ◽  
Probabilistic Measure ◽  
Covering Relation ◽  
Practical Applications ◽  
Variable Precision ◽  
Model Based ◽  
Equivalent Relation ◽  
Proposed Model ◽  
Variable Precision Rough Set

The variable precision probabilistic rough set model is based on equivalent relation and probabilistic measure. However, the requirements of equivalent relation and probabilistic measure are too strict to satisfy in some practical applications. In order to solve the above problem, a variable precision rough set model based on covering relation and uncertainty measure is proposed. Moreover, the upper and lower approximation operators of the proposed model are given, while the properties of the operators are discussed.

Dynamic information aggregation decision-making methods based on variable precision rough set and grey clustering

2014 ◽  
Vol 4 (2) ◽  
pp. 347-361 ◽  
Author(s):  
Yong Liu ◽  
Huan-huan Zhao
Keyword(s):  
Decision Making ◽  
Rough Set ◽  
Information Aggregation ◽  
Dynamic Decision Making ◽  
Dynamic Information ◽  
Content Type ◽  
Variable Precision ◽  
Model Based ◽  
Variable Precision Rough Set ◽  
Decision Making Model

Purpose – The purpose of this paper is to construct a dynamic information aggregation decision-making model based on variable precision rough set. Design/methodology/approach – To deal with the dynamic decision-making problems, the grey relational analysis method, grey fixed weight clustering based on the centre triangle whitening weight function and maximum entropy principle is used to establish the dynamic information aggregation decision-making model based on variable precision rough set. The method, to begin with, the grey relational analysis method is used to determine the attributes weights of each stage; taking the proximity of the attribute measurement value and positive and negative desired effect value and the uncertainty of time weight into account, a multi-objective optimisation model based on maximum entropy principle is established to solve the model with Lagrange multiplier method, so that time weights expression are acquired; what is more, the decision-making attribute is obtained by grey fixed weight clustering based on the centre triangle whitening weight function, so that multi-decision-making table with dynamic characteristics is established, and then probabilistic decision rules from multi-criteria decision table are derived by applying variable precision rough set. Finally, a decision-making model validates the feasibility and effectiveness of the model. Findings – The results show that it the proposed model can well aggregate the multi-stage dynamic decision-making information, realise the extraction of decision-making rules. Research limitations/implications – The method exposed in the paper can be used to deal with the decision-making problems with the multi-stage dynamic characteristics, and decision-making attributes contain noise data and the attribute values are interval grey numbers. Originality/value – The paper succeeds in realising both the aggregation of dynamic decision-making information and the extraction of decision-making rules.

A New Rough Set Model and its Application

2014 ◽  
Vol 599-601 ◽  
pp. 1350-1356
Author(s):  
Ming Ming Jia ◽  
Hai Qin Qin ◽  
Yong Qi Wang ◽  
Ke Jun Xu
Keyword(s):  
Rough Set ◽  
Discrete Variables ◽  
Water Pump ◽  
Variable Precision ◽  
Engineering Problems ◽  
Neighborhood Rough Set ◽  
Variable Precision Rough Set ◽  
Robust To Noise

A new neighborhood variable precision rough set modal is presented in this paper. The modal possesses the characteristics of neighborhood rough set and variable precision rough set, so it can overcome shortcomings of classic rough set which only be fit for discrete variables and sensitive to noise. Based on giving the definitions of approximate reduction, lower and upper approximate reduction, lower and upper distribution reduction, two kinds of algorithms to confirm lower and upper distribution reduction were advanced. The modal was applied to diagnose one frequency modulated water pump vibration faults. The result shows the modal is more suitable to engineering problems, because it can not only deal with continues variables but also be robust to noise.

Incremental Approach for Updating Approximations of Variable Precision Rough Set Based on Dominance Relations

2014 ◽  
Vol 631-632 ◽  
pp. 49-52
Author(s):  
Yan Li ◽  
Jia Jia Hou ◽  
Xiao Qing Liu
Keyword(s):  
Information System ◽  
Rough Set ◽  
Dominance Relation ◽  
Incremental Updating ◽  
Dominance Relations ◽  
Incremental Approach ◽  
Variable Precision ◽  
Variable Precision Rough Set ◽  
Over Time

Variable precision rough set (VPRS) based on dominance relation is an extension of traditional rough set by which can handle preference-ordered information flexibly. This paper focuses on the maintenance of approximations in dominance based VPRS when the objects in an information system vary over time. The incremental updating principles are given as inserting or deleting an object, and some experimental evaluations validates the effectiveness of the proposed method.

Sign in / Sign up

Export Citation Format

Share Document