基于可能性理论的测试信息融合及不确定性处理方法与分析

doi:10.3969/j.issn.1000-1158.2018.01.29

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Abstract Deal with the question of measurement message fusion and uncertainty treatment, a method using conditional possibility distribution to derive the posteriori information about the measurement was proposed. An approach to measurement message fusion and uncertainty treatment in terms of random-fuzzy variables (RFVs) possibility distributions instead of probability distributions was presented. A simple measurement example was also considered to prove the usefulness and effectiveness of the proposed method. The results show that, based on possibility theory, it is possible to obtain a more accurate posteriori estimate of the measurement combining with the reliable measurement priori knowledge.

Key words： metrology measurement message fusion possibility distributions random fuzzy variables uncertainty evaluation

Received: 17 November 2016 Published: 29 December 2017

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	Articles by authors
	YU Xue-feng
	YU Jie
	ZHANG Hong-qing

Cite this article:

YU Xue-feng,YU Jie,ZHANG Hong-qing. Analysis of Measurement Message Fusion and Uncertainty Treatment Based on Possibility Theory[J]. Acta Metrologica Sinica, 2018, 39(1): 140-144.

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http://jlxb.china-csm.org:81/Jwk_jlxb/EN/10.3969/j.issn.1000-1158.2018.01.29 OR http://jlxb.china-csm.org:81/Jwk_jlxb/EN/Y2018/V39/I1/140

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