Determining Basic Probability Assignment Based on the Improved Similarity Measures of Generalized Fuzzy Numbers

  • Wen Jiang
  • Yan Yang Northwestern Polytechnical University School of Electronics and Information, Northwestern Polytechnical University, Xi’an 710072, China
  • Yu Luo Northwestern Polytechnical University School of Electronics and Information, Northwestern Polytechnical University, Xi’an 710072, China
  • Xiyun Qin Northwestern Polytechnical University School of Electronics and Information, Northwestern Polytechnical University, Xi’an 710072, China

Abstract

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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Published
2015-04-28
How to Cite
JIANG, Wen et al. Determining Basic Probability Assignment Based on the Improved Similarity Measures of Generalized Fuzzy Numbers. INTERNATIONAL JOURNAL OF COMPUTERS COMMUNICATIONS & CONTROL, [S.l.], v. 10, n. 3, p. 333-347, apr. 2015. ISSN 1841-9844. Available at: <http://univagora.ro/jour/index.php/ijccc/article/view/1656>. Date accessed: 07 july 2020. doi: https://doi.org/10.15837/ijccc.2015.3.1656.

Keywords

data fusion, dempster-Shafer evidence theory, basic probability assignment (BPA), generalized fuzzy numbers, similarity measures