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Related papers: Conflict Free Rule for Combining Evidences

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This chapter defines a new concept and framework for constructing fusion rules for evidences. This framework is based on a referee function, which does a decisional arbitrament conditionally to basic decisions provided by the several…

Artificial Intelligence · Computer Science 2009-03-30 Frederic Dambreville

These last years, there were many studies on the problem of the conflict coming from information combination, especially in evidence theory. We can summarise the solutions for manage the conflict into three different approaches: first, we…

Artificial Intelligence · Computer Science 2008-12-18 Arnaud Martin , Christophe Osswald

This paper presents two new promising rules of combination for the fusion of uncertain and potentially highly conflicting sources of evidences in the framework of the theory of belief functions in order to palliate the well-know limitations…

Artificial Intelligence · Computer Science 2007-05-23 M. C. Florea , J. Dezert , P. Valin , F. Smarandache , Anne-Laure Jousselme

In this paper a new mathematical procedure is presented for combining different pieces of evidence which are represented in the interval form to reflect our knowledge about the truth of a hypothesis. Evidences may be correlated to each…

Artificial Intelligence · Computer Science 2013-04-05 L. W. Chang , Rangasami L. Kashyap

The theory of belief functions manages uncertainty and also proposes a set of combination rules to aggregate opinions of several sources. Some combination rules mix evidential information where sources are independent; other rules are…

Artificial Intelligence · Computer Science 2015-03-18 Mouna Chebbah , Arnaud Martin , Boutheina Ben Yaghlane

The theory of belief functions is an effective tool to deal with the multiple uncertain information. In recent years, many evidence combination rules have been proposed in this framework, such as the conjunctive rule, the cautious rule, the…

Artificial Intelligence · Computer Science 2017-07-26 Kuang Zhou , Arnaud Martin , Quan Pan

We present and discuss a mixed conjunctive and disjunctive rule, a generalization of conflict repartition rules, and a combination of these two rules. In the belief functions theory one of the major problem is the conflict repartition…

Artificial Intelligence · Computer Science 2008-12-18 Arnaud Martin , Christophe Osswald

In Information fusion, the conflict is an important concept. Indeed, combining several imperfect experts or sources allows conflict. In the theory of belief functions, this notion has been discussed a lot. The mass appearing on the empty…

Artificial Intelligence · Computer Science 2017-09-14 Arnaud Martin

In this chapter, we present and discuss a new generalized proportional conflict redistribution rule. The Dezert-Smarandache extension of the Demster-Shafer theory has relaunched the studies on the combination rules especially for the…

Artificial Intelligence · Computer Science 2008-12-18 Arnaud Martin , Christophe Osswald

Dempster-Shafer theory of evidence is widely applied to uncertainty modelling and knowledge reasoning because of its advantages in dealing with uncertain information. But some conditions or requirements, such as exclusiveness hypothesis and…

Artificial Intelligence · Computer Science 2017-03-16 Xinyang Deng , Wen Jiang

In recent years, the interest in interpretable classification models has grown. One of the proposed ways to improve the interpretability of a rule-based classification model is to use sets (unordered collections) of rules, instead of lists…

Machine Learning · Computer Science 2020-03-31 Thiago Zafalon Miranda , Diorge Brognara Sardinha , Ricardo Cerri

This short paper introduces two new fusion rules for combining quantitative basic belief assignments. These rules although very simple have not been proposed in literature so far and could serve as useful alternatives because of their low…

Artificial Intelligence · Computer Science 2011-12-05 Florentin Smarandache , Jean Dezert

Since no fusion theory neither rule fully satisfy all needed applications, the author proposes a Unification of Fusion Theories and a combination of fusion rules in solving problems/applications. For each particular application, one selects…

Artificial Intelligence · Computer Science 2007-05-23 Florentin Smarandache

The theory of belief functions is widely used for data from multiple sources. Different evidence combination rules have been proposed in this framework according to the properties of the sources to combine. However, most of these…

Artificial Intelligence · Computer Science 2018-10-02 Kuang Zhou , Arnaud Martin , Quan Pan

In this correspondence we study the problem of channel-aware decision fusion when the sensor detection probability is not known at the decision fusion center. Several alternatives proposed in the literature are compared and new fusion rules…

Information Theory · Computer Science 2016-03-11 Domenico Ciuonzo , Pierluigi Salvo Rossi

In this paper we propose a new family of Belief Conditioning Rules (BCRs) for belief revision. These rules are not directly related with the fusion of several sources of evidence but with the revision of a belief assignment available at a…

Artificial Intelligence · Computer Science 2007-05-23 Florentin Smarandache , Jean Dezert

Given that distributed systems face adversarial behaviors such as eavesdropping and cyberattacks, how to ensure the evidence fusion result is credible becomes a must-be-addressed topic. Different from traditional research that assumes nodes…

Cryptography and Security · Computer Science 2024-12-10 Chaoxiong Ma , Yan Liang

In this chapter, we present two applications in information fusion in order to evaluate the generalized proportional conflict redistribution rule presented in the chapter \cite{Martin06a}. Most of the time the combination rules are…

Computer Vision and Pattern Recognition · Computer Science 2008-12-18 Arnaud Martin , Christophe Osswald

When simultaneously reasoning with evidences about several different events it is necessary to separate the evidence according to event. These events should then be handled independently. However, when propositions of evidences are weakly…

Artificial Intelligence · Computer Science 2007-05-23 Johan Schubert

Although evidence integration to the boundary model has successfully explained a wide range of behavioral and neural data in decision making under uncertainty, how animals learn and optimize the boundary remains unresolved. Here, we propose…

Neural and Evolutionary Computing · Computer Science 2024-08-13 Jamal Esmaily , Rani Moran , Yasser Roudi , Bahador Bahrami
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