A novel distance function of D numbers and its application in product engineering

被引：37
作者：
Li, Meizhu [1 ]
Hu, Yong [2 ]
Zhang, Qi [1 ]
Deng, Yong [1 ,3 ,4 ]
机构：
[1] Southwest Univ, Sch Comp & Informat Sci, Chongqing 400715, Peoples R China
[2] Jinan Univ, BDDI, Guangzhou 510006, Guangdong, Peoples R China
[3] Northwestern Polytech Univ, Sch Elect & Informat, Xian 710072, Shaanxi, Peoples R China
[4] Vanderbilt Univ, Sch Engn, Nashville, TN 37235 USA
来源：
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE | 2016年 / 47卷
基金：
中国国家自然科学基金; 国家高技术研究发展计划(863计划);
关键词：
Dempster-Shafer evidence theory; Belief function; Basic probability assignment; D numbers; Distance function; Product engineering; RISK ANALYSIS; FUZZY; DEPENDENCE; MODEL;
D O I：
10.1016/j.engappai.2015.06.004
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
The Dempster-Shafer theory is widely applied in uncertainty modelling and knowledge reasoning due to its ability of expressing uncertain information. A distance between two basic probability assignments (BPAs) presents a measure of performance for identification of algorithms based on the evidential theory of Dempster-Shafer. However, some conditions lead to limitations in practical application for the Dempster-Shafer theory, such as exclusiveness hypothesis and completeness constraint. To overcome these shortcomings, a novel theory called D numbers theory is proposed. A distance function of D numbers is proposed to measure the distance between two D numbers. The distance function of D numbers is a generalization of distance between two BPAs, which inherits the advantage of Dempster-Shafer theory and strengthens the capability of uncertainty modeling. An illustrative case about product engineering is provided to demonstrate the effectiveness of the proposed function. (C) 2015 Elsevier Ltd. All rights reserved.
引用
收藏
页码：61 / 67
页数：7
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