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International Journal of Machine Learning and Cybernetics
Published in: International Journal of Machine Learning and Cybernetics 4/2016

01-08-2016 | Original Article

Optimal decision of multi-inconsistent information systems based on information fusion

Authors: Shaopu Zhang, Tao Feng

Published in: International Journal of Machine Learning and Cybernetics | Issue 4/2016

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Abstract

This paper discusses the fusion of multi-inconsistent decision information systems. First, basic definitions and properties of rough sets, belief and plausibility functions are reviewed. Then, conditional mass function, conditional belief function and conditional plausibility function based on the decision set are defined. We then study the optimal decision of a test set and the reduction of an inconsistent decision information system based on the conditional mass function. Meanwhile, conditional mass function, conditional belief function and conditional plausibility function based on the conditional attribute set are also discussed and we define an uncertainty degree of an inconsistent information system based on the quasi-probability measure. Further, we study fusion method of inconsistent decision information systems using conditional mass functions based on a decision set. Finally, we define a conditional uncertainty measure and give a method to obtain the optimal decision and the confidence level.
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Metadata
Title
Optimal decision of multi-inconsistent information systems based on information fusion
Authors
Shaopu Zhang
Tao Feng
Publication date
01-08-2016
Publisher
Springer Berlin Heidelberg
Published in
International Journal of Machine Learning and Cybernetics / Issue 4/2016
Print ISSN: 1868-8071
Electronic ISSN: 1868-808X
DOI
https://doi.org/10.1007/s13042-015-0441-7

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