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  1. International Journal of Machine Learning and Cybernetics
  2. International Journal of Machine Learning and Cybernetics : Volume 4
  3. International Journal of Machine Learning and Cybernetics : Volume 4, Issue 3, June 2013
  4. Lattice-valued information systems based on dominance relation
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International Journal of Machine Learning and Cybernetics : Volume 8
International Journal of Machine Learning and Cybernetics : Volume 7
International Journal of Machine Learning and Cybernetics : Volume 6
International Journal of Machine Learning and Cybernetics : Volume 5
International Journal of Machine Learning and Cybernetics : Volume 4
International Journal of Machine Learning and Cybernetics : Volume 4, Issue 6, December 2013
International Journal of Machine Learning and Cybernetics : Volume 4, Issue 5, October 2013
International Journal of Machine Learning and Cybernetics : Volume 4, Issue 4, August 2013
International Journal of Machine Learning and Cybernetics : Volume 4, Issue 3, June 2013
An enhanced XCS rule discovery module using feature ranking
Design of custom-made stacked patch antennas: a machine learning approach
On the structure of definable sets in covering approximation spaces
Spatial pooling for greyscale images
Parameter selection algorithm with self adaptive growing neural network classifier for diagnosis issues
Minimizing data consumption with sequential online feature selection
Lattice-valued information systems based on dominance relation
International Journal of Machine Learning and Cybernetics : Volume 4, Issue 2, April 2013
International Journal of Machine Learning and Cybernetics : Volume 4, Issue 1, February 2013
International Journal of Machine Learning and Cybernetics : Volume 3
International Journal of Machine Learning and Cybernetics : Volume 2
International Journal of Machine Learning and Cybernetics : Volume 1

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Lattice-valued information systems based on dominance relation

Content Provider Springer Nature Link
Author Xu, Weihua Liu, Shihu Zhang, Wenxiu
Copyright Year 2012
Abstract In this paper, as a naturally generalization of classical information systems, lattice-valued information systems based on dominance relation is proposed. An approach for ranking all objects in this system is constructed consequently, and decision makers can find objects with better property to make an useful and effective decision. In addition, the rough set approach to lattice-valued information systems based on dominance relation is established. And evidence theories in this system are formulated for the analysis of lattice-valued information systems based on dominance relation. What is more, in order to acquire concise knowledge representation and extract much simpler decision rules, the methods of attribute reductions based on discernibility matrix and evidence theory are investigated carefully. These results will be helpful for decision-making analysis in lattice-valued information systems based on dominance relation.
Starting Page 245
Ending Page 257
Page Count 13
File Format PDF
ISSN 18688071
Journal International Journal of Machine Learning and Cybernetics
Volume Number 4
Issue Number 3
e-ISSN 1868808X
Language English
Publisher Springer-Verlag
Publisher Date 2012-03-11
Publisher Place Berlin, Heidelberg
Access Restriction One Nation One Subscription (ONOS)
Subject Keyword Attribute reduction Dempster–Shafer theory of evidence Dominance relation Lattice-valued information systems Rough set Computational Intelligence Artificial Intelligence (incl. Robotics) Control, Robotics, Mechatronics Statistical Physics, Dynamical Systems and Complexity Systems Biology Pattern Recognition
Content Type Text
Resource Type Article
Subject Artificial Intelligence Computer Vision and Pattern Recognition Software
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