A New Method of Attribute Reduction and Prediction in Fuzzy Decision System

An, Qinli

doi:10.1007/978-3-642-14831-6_7

Qinli An⁵

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 93))

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International Conference on Intelligent Computing

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Abstract

The theory of rough sets has become well established as an approach for uncertainty management in a wide variety of applications. Various fuzzy generalizations of rough approximations have been made over the years. A new framework for the study of low approximation, upper approximation, attribute reduction are defined in fuzzy decision system in which both lower bound reduction, upper bound reduction, bound reduction are given. Rule extraction and prediction are investigated through one example.

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Authors and Affiliations

College of Science, Air Force Engineering University, Xi’an, Shaanxi, 710051, P.R. China
Qinli An

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Qinli An
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Editors and Affiliations

Institute of Intelligent Machines, Chinese Academy of Sciences, Hefei, Anhui,, China
De-Shuang Huang
School of Computing and Intelligent Systems, University of Ulster at Magee Campus, BT48 7JL, Derry, Northern Ireland, UK
Martin McGinnity
Laboratoire LITIS, Université de Rouen, 76800, Saint Etienne du Rouvray, France
Laurent Heutte
Department of Electrical and Computer Engineering, Ryerson University, Toronto, Ontario, Canada
Xiao-Ping Zhang

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An, Q. (2010). A New Method of Attribute Reduction and Prediction in Fuzzy Decision System. In: Huang, DS., McGinnity, M., Heutte, L., Zhang, XP. (eds) Advanced Intelligent Computing Theories and Applications. ICIC 2010. Communications in Computer and Information Science, vol 93. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-14831-6_7

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DOI: https://doi.org/10.1007/978-3-642-14831-6_7
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-14830-9
Online ISBN: 978-3-642-14831-6
eBook Packages: Computer ScienceComputer Science (R0)

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