Open AccessCombination of Evidence in Dempster-Shafer Theory
Author(s) -
Kari Sentz,
Scott Ferson
Publication year - 2002
Publication title -
osti oai (u.s. department of energy office of scientific and technical information)
Language(s) - English
Resource type - Reports
DOI - 10.2172/800792
Subject(s) - dempster–shafer theory , probabilistic logic , reliability (semiconductor) , expert elicitation , interval (graph theory) , probability theory , computer science , representation (politics) , set (abstract data type) , data mining , reliability theory , mathematical theory , artificial intelligence , mathematics , machine learning , statistics , power (physics) , physics , quantum mechanics , combinatorics , politics , failure rate , political science , law , programming language
Dempster-Shafer theory offers an alternative to traditional probabilistic theory for the mathematical representation of uncertainty. The significant innovation of this framework is that it allows for the allocation of a probability mass to sets or intervals. Dempster-Shafer theory does not require an assumption regarding the probability of the individual constituents of the set or interval. This is a potentially valuable tool for the evaluation of risk and reliability in engineering applications when it is not possible to obtain a precise measurement from experiments, or when knowledge is obtained from expert elicitation. An important aspect of this theory is the combination of evidence obtained from multiple sources and the modeling of conflict between them. This report surveys a number of possible combination rules for Dempster-Shafer structures and provides examples of the implementation of these rules for discrete and interval-valued data
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