Information Fusion Based on Information Entropy in Fuzzy Multi-source Incomplete Information System

Information Fusion Based on Information Entropy in Fuzzy Multi-source Incomplete Information System With the development of society, although the way that people get information more and more convenient, the information which people get may be incomplete and has a little degree of uncertainty and fuzziness. In real life, the incomplete fuzzy phenomenon of information source exists widely. It is extremely meaningful to fuse multiple fuzzy incomplete information sources effectively. In this study, a new method is presented for information fusion based on information entropy in fuzzy incomplete information system and the effectiveness of the new method is verified by comparing the average fusion method. Then, an illustrative example is delivered to illustrate the effectiveness of the proposed fusion method. Finally, we have also tested the veracity and validity of this method by experiment on a dataset from UCI. The results of this study will be useful for pooling the uncertain data from different information sources and significant for establishing a distinct direction of the fusion method. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Fuzzy Systems Springer Journals

Information Fusion Based on Information Entropy in Fuzzy Multi-source Incomplete Information System

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Publisher
Springer Berlin Heidelberg
Copyright
Copyright © 2016 by Taiwan Fuzzy Systems Association and Springer-Verlag Berlin Heidelberg
Subject
Engineering; Computational Intelligence; Artificial Intelligence (incl. Robotics); Operations Research, Management Science
ISSN
1562-2479
eISSN
2199-3211
D.O.I.
10.1007/s40815-016-0230-9
Publisher site
See Article on Publisher Site

Abstract

With the development of society, although the way that people get information more and more convenient, the information which people get may be incomplete and has a little degree of uncertainty and fuzziness. In real life, the incomplete fuzzy phenomenon of information source exists widely. It is extremely meaningful to fuse multiple fuzzy incomplete information sources effectively. In this study, a new method is presented for information fusion based on information entropy in fuzzy incomplete information system and the effectiveness of the new method is verified by comparing the average fusion method. Then, an illustrative example is delivered to illustrate the effectiveness of the proposed fusion method. Finally, we have also tested the veracity and validity of this method by experiment on a dataset from UCI. The results of this study will be useful for pooling the uncertain data from different information sources and significant for establishing a distinct direction of the fusion method.

Journal

International Journal of Fuzzy SystemsSpringer Journals

Published: Jul 25, 2016

References

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