Abstract
A distance or dissimilarity of evidence represents the degree of dissimilarity between bodies of evidence, which has been widely used in the applications based on belief functions theory. In this paper, new distance measures are proposed based on belief intervals [Bel, Pl]. For a basic belief assignment (BBA), the belief intervals of different focal elements are first calculated, respectively, which can be considered as interval numbers. Then, according to the distance of interval numbers, we can calculate the distance values between the corresponding belief intervals of the same focal elements in two given BBAs. Based on these distance values of belief intervals, new distance measures of evidence can be obtained using Euclidean and Chebyshev approaches, respectively. Some experiments and related analyses are provided to show the rationality and efficiency of the proposed measures.
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Han, D., Dezert, J., Yang, Y. (2014). New Distance Measures of Evidence Based on Belief Intervals. In: Cuzzolin, F. (eds) Belief Functions: Theory and Applications. BELIEF 2014. Lecture Notes in Computer Science(), vol 8764. Springer, Cham. https://doi.org/10.1007/978-3-319-11191-9_47
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DOI: https://doi.org/10.1007/978-3-319-11191-9_47
Publisher Name: Springer, Cham
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