Paper Info
Title
Algorithms for Different Approximations in Incomplete Information Systems with Maximal Compatible Classes as Primitive Granules
Abstract
This paper proposes some expanded rough set models with maximal compatible classes as primitive granules, introduces two new granules for extending rough set model, and designs algorithms to solve maximal compatible classes, to find the lower and upper approximations according to the newly granules, to compute reducts and minimal reducts with attribute significance. It also verifies the validity of algorithms by examples. These provide an important and implemental theoretical base for rough set theory to deal with problems in incomplete information systems.
Year
DOI
Venue
2007
10.1109/GrC.2007.58
GrC
Keywords
Field
DocType
rough set theory,incomplete information systems,maximal compatible classes,minimal reducts,attribute significance,different approximations,primitive granules,key word,designs algorithm,primitive granule,rough set model,implemental theoretical base,incomplete information system,expanded rough set model,maximal compatible class,rough set,incomplete information
Incomplete information system,Compatibility (mechanics),Computer science,Algorithm,Rough set,Dominance-based rough set approach
Conference
ISBN
Citations 
PageRank 
978-0-7695-3032-1
1
0.43
References 
Authors
11
5
Name
Order
Citations
PageRank
Chen Wu1696.20
Xiaohua Hu22819314.15
Zhoujun Li3964115.99
Xiaohua Zhou443825.82
Palakorn Achananuparp530223.16