Related family: A new method for attribute reduction of covering information systems

2013 ◽  
Vol 228 ◽  
pp. 175-191 ◽  
Author(s):  
Tian Yang ◽  
Qingguo Li ◽  
Bilei Zhou
Keyword(s):  
Information Systems ◽  
Attribute Reduction ◽  
New Method ◽  
Related Family

scholarly journals Lower Approximation Reduction Based on Discernibility Information Tree in Inconsistent Ordered Decision Information Systems

Symmetry ◽  
2018 ◽  
Vol 10 (12) ◽  
pp. 696 ◽  
Author(s):  
Jia Zhang ◽  
Xiaoyan Zhang ◽  
Weihua Xu
Keyword(s):  
Information System ◽  
Information Systems ◽  
Set Theory ◽  
Rough Set ◽  
Rough Set Theory ◽  
Attribute Reduction ◽  
Common Method ◽  
New Method ◽  
Lower Approximation ◽  
Dominance Relations

Attribute reduction is an important topic in the research of rough set theory, and it has been widely used in many aspects. Reduction based on an identifiable matrix is a common method, but a lot of space is occupied by repetitive and redundant identifiable attribute sets. Therefore, a new method for attribute reduction is proposed, which compresses and stores the identifiable attribute set by a discernibility information tree. In this paper, the discernibility information tree based on a lower approximation identifiable matrix is constructed in an inconsistent decision information system under dominance relations. Then, combining the lower approximation function with the discernibility information tree, a complete algorithm of lower approximation reduction based on the discernibility information tree is established. Finally, the rationality and correctness of this method are verified by an example.

scholarly journals A Model for Selecting a Strategic Information System Using the FITradeoff

2016 ◽  
Vol 2016 ◽  
pp. 1-7 ◽  
Author(s):  
Ana Paula Henriques de Gusmão ◽  
Cristina Pereira Medeiros
Keyword(s):  
Information System ◽  
Information Systems ◽  
Decision Maker ◽  
Additive Model ◽  
New Method ◽  
Strategic Information ◽  
Perceived Need ◽  
Using Data ◽  
Strategic Information System ◽  
Glass Packaging

This paper arose from the perceived need to make a contribution towards assessing a strategic information system by using a new method for eliciting the weights of criteria. This is considered one of the most complex and important stages in multicriteria models. Multicriteria models have been proposed to support decisions in the context of information systems given that problems in this field deal with many conflicting criteria. The new procedure for eliciting the weights of the criteria has the advantage of requiring less effort from the decision-maker and, thus, the risk of inconsistent answers is minimized. Therefore, a model based on this new procedure is proposed and applied using data from a glass packaging factory that needs to select a single information system from a set of systems previously identified as relevant. The results obtained are consistent both with the performance of alternatives and with the additive model used to evaluate the alternatives.

On variable-precision-based rough set approach to incomplete interval-valued fuzzy information systems and its applications

2021 ◽  
Vol 40 (1) ◽  
pp. 463-475
Author(s):  
Juan Li ◽  
Yabin Shao ◽  
Xiaoding Qi
Keyword(s):  
Information System ◽  
Information Systems ◽  
Attribute Reduction ◽  
Misclassification Rate ◽  
Fuzzy Information ◽  
Attribute Weights ◽  
Variable Precision ◽  
Multiple Attribute ◽  
Rough Approximation ◽  
Interval Valued

 With respect to multiple attribute group decision making problems in which the attribute weights and the expert weights take the form of real numbers and the attribute values take the form of interval-valued uncertain linguistic variable. In this paper, we introduce the idea of variable precision into the incomplete interval-valued fuzzy information system and propose the theory of variable precision rough sets over incomplete interval-valued fuzzy information systems. Then, we give the properties of rough approximation operators and study the knowledge discovery and attribute reduction in the incomplete interval-valued fuzzy information system under the condition that a certain degree of misclassification rate is allowed to exist. Furthermore, a decision rule and decision model are given. Finally, an illustrative example is given and compared with the existing methods, the practicability and effectiveness of this method are further verified.

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