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International Journal for Uncertainty Quantification
インパクトファクター: 3.259 5年インパクトファクター: 2.547 SJR: 0.531 SNIP: 0.8 CiteScore™: 1.52

ISSN 印刷: 2152-5080
ISSN オンライン: 2152-5099

Open Access

International Journal for Uncertainty Quantification

DOI: 10.1615/Int.J.UncertaintyQuantification.2016016572
pages 157-165

CONSTRUCTION OF EVIDENCE BODIES FROM UNCERTAIN OBSERVATIONS

Liang Zhao
School of Information Engineering, Southwest University of Science and Technology, MianYang, 621010, China
Zhanping Yang
Institute of Electronic Engineering, China Academy of Engineering Physics, MianYang, 621900, China
Longyuan Xiao
Institute of Electronic Engineering, China Academy of Engineering Physics, MianYang, 621900, China

要約

The construction of evidence bodies is a key issue when the evidence theory is applied in uncertainty quantification. The existing approaches proposed for this topic are usually too subjective to obtain rational evidence bodies in the situation of uncertain observations. This paper introduces a repeated kernel-density-estimation based approach for constructing evidence bodies from uncertain observations. The typical uncertain observations-limited point measurements together with interval measurements are considered in this paper. Using kernel density estimation with a loop, a family of probability distribution about the given observations is obtained, the probability box characterized by the bounds of the probability distribution family is discretized to evidence bodies by an outer discretization method. The approach also considers the uncertainty in the distribution assumption during the kernel density estimation. A numerical example is used to demonstrate the proposed approach.


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