Fusion of sources of evidence with different importances and reliabilities

Smarandache, F.; Dezert, Jean; Tacnet, Jean‐Marc

doi:10.1109/icif.2010.5712071

Cited by 88 publications

(96 citation statements)

References 6 publications

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“…In reliability discounting a discounting factor α in [0, 1] can be applied to characterize the quality of an evidence source [7]. For instance, evidence extracted from an aviation journal is considered higher quality than a blog post.…”

Section: Reliability Discounting Techniquesmentioning

confidence: 99%

“…Reliability can be viewed as an objective property of an evidence source whereas priority is viewed as a subjective property expressed by an expert [7]. Counter-intuitive results could be obtained if unequal sources are fused and these factors are not taken into consideration.…”

Section: Introductionmentioning

confidence: 99%

“…Counter-intuitive results could be obtained if unequal sources are fused and these factors are not taken into consideration. To highlight the importance of all this in the decision making process we apply two discounting techniques: reliability discounting using Shafer's classical discounting approach and priority discounting based on the importance discounting technique [7]. We construct a maximal consistent subset to aid in defining where discounting should be applied.…”

Section: Introductionmentioning

confidence: 99%

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Application of Evidence Theory and Discounting Techniques to Aerospace Design

Browne

Bell

Liu

et al. 2012

Communications in Computer and Information Science

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Abstract. Critical decisions are made by decision-makers throughout the life-cycle of large-scale projects. These decisions are crucial as they have a direct impact upon the outcome and the success of projects. To aid decision-makers in the decision making process we present an evidential reasoning framework. This approach utilizes the Dezert-Smarandache theory to fuse heterogeneous evidence sources that suffer from levels of uncertainty, imprecision and conflicts to provide beliefs for decision options. To analyze the impact of source reliability and priority upon the decision making process, a reliability discounting technique and a priority discounting technique, are applied. A maximal consistent subset is constructed to aid in defining where discounting should be applied. Application of the evidential reasoning framework is illustrated using a case study based in the Aerospace domain.

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Section: Reliability Discounting Techniquesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Application of Evidence Theory and Discounting Techniques to Aerospace Design

Browne

Bell

Liu

et al. 2012

Communications in Computer and Information Science

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“…Hence, DS theory cannot combine two pieces of evidence in complete conflict [19]. To address this problem, Dezert et al [20,21] developed the Dezert-Smarandache Theory (DSmT) by introducing coefficient of reliabilities and weights, and makes the DSmT capable of combining pieces of evidence in complete confliction by redistributing the conflicts of evidences. However, DSmT neither keeps the consistencies with the Bayesian rule, nor is acknowledged as rigorous reasoning [22].…”

Section: A Proposed Approachmentioning

confidence: 99%

“…In addition, the reliability is associated with evidence e i , denoted by r i , which represents the ability of the evidence, where e i is generated, to provide a correct assessment or solution for a given problem [21]. The reliability of a piece of evidence is the inherent property of the evidence, and in the ER framework it measures the degree of support for, or opposition to, a proposition given that the Symmetry 2017, 9, 186 6 of 15 evidence points to the proposition.…”

Section: Step 3: Conjunctive Inferencementioning

confidence: 99%

An Internet of Things Approach for Extracting Featured Data Using AIS Database: An Application Based on the Viewpoint of Connected Ships

Malekian

et al. 2017

Symmetry

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Automatic Identification System (AIS), as a major data source of navigational data, is widely used in the application of connected ships for the purpose of implementing maritime situation awareness and evaluating maritime transportation. Efficiently extracting featured data from AIS database is always a challenge and time-consuming work for maritime administrators and researchers. In this paper, a novel approach was proposed to extract massive featured data from the AIS database. An Evidential Reasoning rule based methodology was proposed to simulate the procedure of extracting routes from AIS database artificially. First, the frequency distributions of ship dynamic attributes, such as the mean and variance of Speed over Ground, Course over Ground, are obtained, respectively, according to the verified AIS data samples. Subsequently, the correlations between the attributes and belief degrees of the categories are established based on likelihood modeling. In this case, the attributes were characterized into several pieces of evidence, and the evidence can be combined with the Evidential Reasoning rule. In addition, the weight coefficients were trained in a nonlinear optimization model to extract the AIS data more accurately. A real life case study was conducted at an intersection waterway, Yangtze River, Wuhan, China. The results show that the proposed methodology is able to extract data very precisely.

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Canonical decomposition of dichotomous basic belief assignment

Dezert

Smarandache

2020

Int J Intell Syst

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In this paper, we prove that any dichotomous basic belief assignment (BBA) m can be expressed as the combination of two simple belief assignments m p and m c called, respectively, the pros and cons BBAs thanks to the proportional conflict redistribution rule no 5 (PCR5). This decomposition always exists and is unique and we call it the canonical decomposition of the BBA m. We also show that canonical decompositions do not exist in general if we use the conjunctive rule, the disjunctive rule, Dempster's rule, Dubois and Prade's or Yager's rules, or even the averaging rule of combination. We give some numerical examples of canonical decompositions and discuss of the potential interest of this canonical decomposition for applications in information fusion. K E Y W O R D Sbelief functions, canonical decomposition, contra-evidence, PCR5 rule, pro-evidence ‡ ‡ ‡ ‡ We use classical Shafer's discounting method. 1 § § § § That is, cognitively independent.How to cite this article: Dezert J, Smarandache F. Canonical decomposition of dichotomous basic belief assignment. Int J Intell

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Fusion of sources of evidence with different importances and reliabilities

Cited by 88 publications

References 6 publications

Application of Evidence Theory and Discounting Techniques to Aerospace Design

Application of Evidence Theory and Discounting Techniques to Aerospace Design

An Internet of Things Approach for Extracting Featured Data Using AIS Database: An Application Based on the Viewpoint of Connected Ships

Canonical decomposition of dichotomous basic belief assignment

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