Title | ||
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Using Z-number to measure the reliability of new information fusion method and its application in pattern recognition |
Abstract | ||
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Information fusion has traditionally been a concern. In the fusion process, how to effectively take care of the ambiguity and uncertainty of data is a fascinating problem. Dempster-Shafer evidence theory shows powerful functions in dealing with uncertainty information, and Z-number can comprehensively model the ambiguity and reliability of information. Inspired by this, this paper proposed a new information fusion method based on Dempster-Shafer theory and K-means clustering and it established the reliability evaluation criterion based on Z-number. Comparison and discussion verify the rationality of the proposed method, which also illustrates the method has better robustness and sensitivity than existing methods, some critical issues in DST, e.g., conflict management, evidence stuck, are well investigated and overcome by the proposed method. Number examples and the application further shows the application potential of the proposed method in a data-driven intelligent system. (C) 2021 Elsevier B.V. All rights reserved. |
Year | DOI | Venue |
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2021 | 10.1016/j.asoc.2021.107658 | APPLIED SOFT COMPUTING |
Keywords | DocType | Volume |
Information fusion, Dempster-Shafer evidence theory, Z-number, K-means clustering, Target Recognition | Journal | 111 |
ISSN | Citations | PageRank |
1568-4946 | 1 | 0.35 |
References | Authors | |
0 | 5 |
Name | Order | Citations | PageRank |
---|---|---|---|
Ye Tian | 1 | 1 | 0.35 |
Xiangjun Mi | 2 | 6 | 3.44 |
Huizi Cui | 3 | 4 | 1.39 |
Pengdan Zhang | 4 | 1 | 1.03 |
Bingyi Kang | 5 | 1 | 1.70 |