期刊
INTERNATIONAL JOURNAL OF COMPUTERS COMMUNICATIONS & CONTROL
卷 10, 期 3, 页码 333-347出版社
CCC PUBL-AGORA UNIV
DOI: 10.15837/ijccc.2015.3.1656
关键词
data fusion; dempster-Shafer evidence theory; basic probability assignment (BPA); generalized fuzzy numbers; similarity measures
资金
- National Natural Science Foundation of China [61104214]
- Foundation for Fundament Research of Northwestern Polytechnical University [JC20120235]
Dempster-Shafer theory of evidence has been widely used in many data fusion application systems. However, how to determine basic probability assignment, which is the main and the first step in evidence theory, is still an open issue. In this paper, an improved method to determine the similarity measure between generalized fuzzy numbers is presented. The proposed method can overcome the drawbacks of the existing similarity measures. Then, we propose a new method for obtaining basic probability assignment (BPA) based on the proposed similarity measure method between generalized fuzzy numbers. Finally, the efficiency of the proposed method is illustrated by the classification of Iris data.
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