Dynamic fuzzy neighborhood rough set approach for interval-valued information systems with fuzzy decision

2021 ◽  
pp. 107679
Author(s):  
Lei Yang ◽  
Keyun Qin ◽  
Binbin Sang ◽  
Weihua Xu
Keyword(s):  
Information Systems ◽  
Rough Set ◽  
Fuzzy Decision ◽  
Neighborhood Rough Set ◽  
Interval Valued

scholarly journals Multiple Granulation Rough Set Approach to Interval-Valued Intuitionistic Fuzzy Ordered Information Systems

Symmetry ◽  
2021 ◽  
Vol 13 (6) ◽  
pp. 949
Author(s):  
Zhen Li ◽  
Xiaoyan Zhang
Keyword(s):  
Information Theory ◽  
Pattern Recognition ◽  
Information System ◽  
Information Systems ◽  
Rough Set ◽  
Fuzzy Set ◽  
Equivalence Relation ◽  
Target Concept ◽  
Actual Case ◽  
Interval Valued

As a further extension of the fuzzy set and the intuitive fuzzy set, the interval-valued intuitive fuzzy set (IIFS) is a more effective tool to deal with uncertain problems. However, the classical rough set is based on the equivalence relation, which do not apply to the IIFS. In this paper, we combine the IIFS with the ordered information system to obtain the interval-valued intuitive fuzzy ordered information system (IIFOIS). On this basis, three types of multiple granulation rough set models based on the dominance relation are established to effectively overcome the limitation mentioned above, which belongs to the interdisciplinary subject of information theory in mathematics and pattern recognition. First, for an IIFOIS, we put forward a multiple granulation rough set (MGRS) model from two completely symmetry positions, which are optimistic and pessimistic, respectively. Furthermore, we discuss the approximation representation and a few essential characteristics for the target concept, besides several significant rough measures about two kinds of MGRS symmetry models are discussed. Furthermore, a more general MGRS model named the generalized MGRS (GMGRS) model is proposed in an IIFOIS, and some important properties and rough measures are also investigated. Finally, the relationships and differences between the single granulation rough set and the three types of MGRS are discussed carefully by comparing the rough measures between them in an IIFOIS. In order to better utilize the theory to realistic problems, an actual case shows the methods of MGRS models in an IIFOIS is given in this paper.

Rough set theory for the interval-valued fuzzy information systems

2008 ◽  
Vol 178 (8) ◽  
pp. 1968-1985 ◽  
Author(s):  
Zengtai Gong ◽  
Bingzhen Sun ◽  
Degang Chen
Keyword(s):  
Information Systems ◽  
Set Theory ◽  
Rough Set ◽  
Rough Set Theory ◽  
Fuzzy Information ◽  
Interval Valued

scholarly journals A rough set approach for the discovery of classification rules in interval-valued information systems

2008 ◽  
Vol 47 (2) ◽  
pp. 233-246 ◽  
Author(s):  
Yee Leung ◽  
Manfred M. Fischer ◽  
Wei-Zhi Wu ◽  
Ju-Sheng Mi
Keyword(s):  
Information Systems ◽  
Rough Set ◽  
Classification Rules ◽  
Interval Valued

scholarly journals Rough Set Approach to Approximation Reduction in Ordered Decision Table with Fuzzy Decision

2011 ◽  
Vol 2011 ◽  
pp. 1-16 ◽  
Author(s):  
Xiaoyan Zhang ◽  
Shihu Liu ◽  
Weihua Xu
Keyword(s):  
Information Systems ◽  
Knowledge Discovery ◽  
Rough Set ◽  
Decision Table ◽  
Fuzzy Decision ◽  
Efficient Tool ◽  
Lower Approximation ◽  
Dominance Relations ◽  
Decision Tables

In practice, some of information systems are based on dominance relations, and values of decision attribute are fuzzy. So, it is meaningful to study attribute reductions in ordered decision tables with fuzzy decision. In this paper, upper and lower approximation reductions are proposed in this kind of complicated decision table, respectively. Some important properties are discussed. The judgement theorems and discernibility matrices associated with two reductions are obtained from which the theory of attribute reductions is provided in ordered decision tables with fuzzy decision. Moreover, rough set approach to upper and lower approximation reductions is presented in ordered decision tables with fuzzy decision as well. An example illustrates the validity of the approach, and results show that it is an efficient tool for knowledge discovery in ordered decision tables with fuzzy decision.

Variable-precision-dominance-based rough set approach to interval-valued information systems

2013 ◽  
Vol 244 ◽  
pp. 75-91 ◽  
Author(s):  
Hong-Ying Zhang ◽  
Yee Leung ◽  
Lei Zhou
Keyword(s):  
Information Systems ◽  
Rough Set ◽  
Variable Precision ◽  
Interval Valued

KNOWLEDGE REDUCTION IN LATTICE-VALUED INFORMATION SYSTEMS WITH INTERVAL-VALUED INTUITIONISTIC FUZZY DECISION

2013 ◽  
Vol 22 (01) ◽  
pp. 1250030 ◽  
Author(s):  
WEI-HUA XU ◽  
SHI-HU LIU ◽  
FU-SHENG YU
Keyword(s):  
Information Systems ◽  
Lattice Theory ◽  
Fuzzy Decision ◽  
Discernibility Matrix ◽  
Knowledge Reduction ◽  
Intuitionistic Fuzzy ◽  
Complex Information ◽  
Sets Theory ◽  
Consistent Information ◽  
Interval Valued

In this paper, associated with dominance relation, lattice theory and intuitionistic fuzzy sets theory, the lattice-valued information systems with interval-valued intuitionistic fuzzy decision are proposed and some of its properties are investigated carefully. And, an approach to knowledge reduction based on discernibility matrix in consistent lattice-valued information systems with interval-valued intuitionistic fuzzy decision is constructed and an illustrative example is applied to show its validity. Moreover, extended from the idea of knowledge reduction in consistent information systems, four types of reductions and approaches to obtaining the knowledge reductions of the inconsistent lattice-valued information systems with interval-valued intuitionistic fuzzy decision are formulated via the use of discernibility matrix. Furthermore, examples are considered to show that the approaches are useful and effective. One can obtain that the research is meaningful both in theory and in application for the issue of knowledge reduction in complex information systems.

Using a rough set model to extract rules in dominance-based interval-valued intuitionistic fuzzy information systems

2013 ◽  
Vol 221 ◽  
pp. 215-229 ◽  
Author(s):  
Bing Huang ◽  
Da-kuan Wei ◽  
Hua-xiong Li ◽  
Yu-liang Zhuang
Keyword(s):  
Information Systems ◽  
Rough Set ◽  
Fuzzy Information ◽  
Intuitionistic Fuzzy ◽  
Interval Valued
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