A novel distance function of D numbers and its application in product engineering
Autor: | Qi Zhang, Yong Deng, Yong Hu, Meizhu Li |
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Rok vydání: | 2016 |
Předmět: |
0209 industrial biotechnology
Computer science Generalization 02 engineering and technology Function (mathematics) Measure (mathematics) Product engineering Constraint (information theory) Identification (information) 020901 industrial engineering & automation Artificial Intelligence Control and Systems Engineering Product (mathematics) Completeness (order theory) Metric (mathematics) 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Electrical and Electronic Engineering Completeness (statistics) Algorithm |
Zdroj: | Engineering Applications of Artificial Intelligence. 47:61-67 |
ISSN: | 0952-1976 |
DOI: | 10.1016/j.engappai.2015.06.004 |
Popis: | 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. HighlightsA distance function between two D numbers is proposed and applied in product engineering.The function is effective when elements in the frame of discernment aren't mutually exclusive. |
Databáze: | OpenAIRE |
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