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Bayesian networks implementation of the Dempster Shafer theory to model reliability uncertainty

C. Simon, P. Weber
2006 First International Conference on Availability, Reliability and Security (ARES'06)  
In this paper, the implementation of the Dempster Shafer theory in a Bayesian Network tool is proposed in order to compute system reliability and manage epistemic uncertainty propagation.  ...  Probabilistic tools badly handle these kinds of problems thus, it is better to use formalism from the evidence theory.  ...  The paper has shown how basic concepts of the Dempster Shafer Theory can be implemented in Bayesian Networks tool to manage this kind of uncertainty and to extract the most of information from available  ... 
doi:10.1109/ares.2006.38 dblp:conf/IEEEares/SimonW06 fatcat:lhos5swjurb5zhdne23gncbl3e

Bayesian networks inference algorithm to implement Dempster Shafer theory in reliability analysis

C. Simon, P. Weber, A. Evsukoff
2008 Reliability Engineering & System Safety  
Dempster Shafer theory to treat epistemic uncertainty in reliability analysis is then discussed and its basic concepts that can be applied thanks to the Bayesian network inference algorithm are introduced  ...  Finally, it is shown, with a numerical example, how Bayesian networks' inference algorithms compute complex system reliability and what the Dempster Shafer theory can provide to reliability analysis.  ...  The paper shows how basic concepts of the Dempster Shafer theory can be implemented in Bayesian networks tools to treat this kind of uncertainty and to extract the most of information from the available  ... 
doi:10.1016/j.ress.2007.03.012 fatcat:dvklyp7quzch7jtkpc77d5atf4

Subject index to volume 2

1988 International Journal of Approximate Reasoning  
uncertainty and temporal relationships in, 337 Autonomous agents, centrality of, in theories of action under uncertainty, 303-326 Backward chaining, with fuzzy goals and rules, 108 Bayes belief network  ...  plasminogen activator, 342 Bayesian belief networks, 337 stochastic stimulation of, 331 Bayesian inference, in model-based machine vision, 327-328 Bayesian prediction, for artificial intelligence, 342  ...  calculi, 328-329 Network flow models, with fuzzy auxiliary edge and vertex, 103 Nillson's probabilistic entailment, extended to Dempster-Shafer theory, 339-340 Noise, connectionist expert system  ... 
doi:10.1016/0888-613x(88)90114-4 fatcat:rj373wy2pzff3d3otqdhxs2gca

Heterogeneous Multi-sensor Fusion Based on an Evidential Network for Fall Detection [chapter]

Paulo Armando Cavalcante Aguilar, Jerome Boudy, Dan Istrate, Hamid Medjahed, Bernadette Dorizzi, João Cesar Moura Mota, Jean Louis Baldinger, Toufik Guettari, Imad Belfeki
2011 Lecture Notes in Computer Science  
Among multi-sensor data fusion techniques, Bayesian methods and evidence theories such as Dempster-Shafer Theory (DST), are commonly used to handle the degree of uncertainty in the fusion processes.  ...  The multi-sensor fusion can provide more accurate and reliable information compared to information from each sensor separately taken.  ...  Acknowledgment This research is funded by the FP7 European Project IST-Companion.  ... 
doi:10.1007/978-3-642-21535-3_42 fatcat:rtlea3gvuzbefbg4ch6sjhh4li

Fusion of high resolution optical and SAR images with vector data bases for change detection

Vincent Poulain, Jordi Inglada, Marc Spigai, Jean-Yves Tourneret, Philippe Marthon
2009 2009 IEEE International Geoscience and Remote Sensing Symposium  
Various frameworks are adapted to information fusion, like bayesian probability theory, possibility theory or Dempster-Shafer theory.  ...  Dempster-Shafer theory allows one to assign a mass to A ∪ B, where A and B are two hypotheses that cannot be distinguished, contrary to Bayesian probability theory.  ... 
doi:10.1109/igarss.2009.5417537 dblp:conf/igarss/PoulainISTM09 fatcat:6akbz3pn3rad7izt265bjsqpjy

Survey of Uncertainty Handling in Cloud Service Discovery and Composition

Nouha Khediri, Montaceur Zaghdoud
2014 International Journal on Cloud Computing Services and Architecture  
A set of existing approaches in literature are reviewed and categorized according to the risk modeling.  ...  In addition, the need to treat uncertainty in cloud service discovery and composition induces a lot of concerns in order to minimize the risk.  ...  As for the theory of Dempster-Shafer, its masses are assigned to the entire non-empty subsets of the entities that comprise a system.  ... 
doi:10.5121/ijccsa.2014.4601 fatcat:4f73twfdrvgqhlpwelb6a27kwy

Bayesian Networks and Evidence Theory to Model Complex Systems Reliability

Christophe Simon, Philippe Weber, Eric Levrat
2007 Journal of Computers  
We propose to adapt the Bayesian Network model of reliability in order to integrate the evidence theory and then to produce an Evidential Network.  ...  This paper deals with the use of Bayesian Networks to compute system reliability of complex systems under epistemic uncertainty.  ...  The paper shows how basic concepts of the Dempster Shafer Theory can be implemented in Bayesian Networks tools to treat this kind of uncertainty and to extract the most of information from the available  ... 
doi:10.4304/jcp.2.1.33-43 fatcat:qg2n7imvkbgh5o3pneuywdwxcm

Dempster-Shafer Theory for Intrusion Detection in Ad Hoc Networks

T.M. Chen, V. Venkataramanan
2005 IEEE Internet Computing  
The Dempster-Shafer theory of evidence is well suited for this type of problem because it reflects uncertainty.  ...  The authors review the Dempster-Shafer theory in the context of distributed intrusion detection and demonstrate the theory's usefulness.  ...  Dempster-Shafer Formalities The Dempster-Shafer theory is appealing partly because it can handle uncertainty or ignorancethat is, the lack of knowledge of the complete probabilistic model required for  ... 
doi:10.1109/mic.2005.123 fatcat:pj4ch72lrvcybjtsnk2dkb6osa

Review of Uncertainty Reasoning Approaches as Guidance for Maritime and Offshore Safety-Based Assessment

J. Liu, J.B. Yang, J. Wang, H.S. Sii
2002 The journal of the Safety and Reliability Society  
In this paper we review some of the most important ones, i.e., Bayesian theory of probability, Dempster-Shafer theory of evidence, and fuzzy set theory, describe how they work and in what ways they differ  ...  The study is intended to provide guidance in the process of developing frameworks for safety-based decision analysis using different methods for reasoning under uncertainty.  ...  Acknowledgements This work forms part of the projects supported by the UK Engineering and Physical Sciences Research Council (EPSRC) under Grant References GR/R30624 and GR/R32413.  ... 
doi:10.1080/09617353.2002.11690751 fatcat:2dx7qpb2yng3vd3fzhq44dl7da

Uncertainty in Ontologies: Dempster-Shafer Theory for Data Fusion Applications [article]

Amandine Bellenger, Sylvain Gatepaille
2011 arXiv   pre-print
Therefore, we constructed a Dempster-Shafer ontology that can be imported into any specific domain ontology and that enables us to instantiate it in an uncertain manner.  ...  In addition, uncertainty is perhaps one of the most important characteristics of the data and information handled by Data Fusion.  ...  ACKNOWLEDGMENT We are grateful to Arnaud Saval and Khaled Khelif for their comments and hope that the revised paper has addressed their concerns.  ... 
arXiv:1106.3876v1 fatcat:4g2lxfrzevdtjhk5pum74rnycq

A logic-based analysis of Dempster-Shafer theory

Gregory M. Provan
1990 International Journal of Approximate Reasoning  
Dempster-Shafer theory can be modeled in terms of propositional logic by the tuple (~, p), where S is a set of propositional clauses and p is an assignment of mass to each clause Ei c ~.  ...  Dempster-Shafer (DS) theory is formulated in terms of propositional logic, using the implicit notion of provability underlying DS theory.  ...  This paper shows the relationships between a particular uncertainty calculus, Dempster Shafer theory, and propositional logic, in an effort to assess the adequacy of Dempster Shafer theory as a knowledge  ... 
doi:10.1016/0888-613x(90)90016-u fatcat:sz3hrlzlwzcordumeyror4k7bi

Using the Dempster-Shafer Theory of Evidence to Resolve ABox Inconsistencies [chapter]

Andriy Nikolov, Victoria Uren, Enrico Motta, Anne de Roeck
2008 Lecture Notes in Computer Science  
The Dempster-Shafer theory of evidence is a formalism, which allows appropriate interpretation of extractors' confidence values.  ...  The paper presents an algorithm for translating the subontologies containing conflicts into belief propagation networks and repairing conflicts based on the Dempster-Shafer plausibility.  ...  This work was funded by the X-Media project (www.x-media-project.org) sponsored by the European Commission as part of the Information Society Technologies (IST) programme under EC grant number IST-FP6-  ... 
doi:10.1007/978-3-540-89765-1_9 fatcat:5arz3g5yina37lyezqj6zie4iy

Bayesian and Dempster–Shafer reasoning for knowledge-based fault diagnosis–A comparative study

K. Verbert, R. Babuška, B. De Schutter
2017 Engineering applications of artificial intelligence  
are handled in two well-known frameworks, namely the Bayesian and the Dempster-Shafer reasoning framework.  ...  In contrast to previous works, which take the reasoning method as the starting point, we start from the application, knowledge-based fault diagnosis, and examine the effectiveness of different reasoning  ...  Reasoning in D-S networks We adopt Smets' Transferable Belief Model (TBM) interpretation of the Dempster-Shafer theory [30] .  ... 
doi:10.1016/j.engappai.2017.01.011 fatcat:xx2xgzqx3rbtbjuy3c5qputea4

Evidential Network-Based Multimodal Fusion for Fall Detection

Paulo Armando Cavalcante Aguilar, Jerome Boudy, Dan Istrate, Hamid Medjahed, Bernadette Dorizzi, João Cesar Moura Mota, Jean Louis Baldinger, Toufik Guettari, Imad Belfeki
2013 International Journal of E-Health and Medical Communications (IJEHMC)  
Among multisensor data fusion techniques, Bayesian methods and evidence theories such as Dempster-Shafer Theory (DST), are commonly used to handle the degree of uncertainty in the fusion processes.  ...  The multi-sensor fusion can provide more accurate and reliable information compared to information from each sensor separately taken.  ...  ACKNOWLEDGMENT This research is funded by the FP7 European Project IST-CompanionAble (www.companionable.net).  ... 
doi:10.4018/jehmc.2013010105 fatcat:ioyojn6s5ja4pc7yj6g52jyyfm

Implementation of Efficient Artificial Neural Network Data Fusion Classification Technique for Induction Motor Fault Detection

S. Altaf, Sensor Network and Smart Environment Research Centre, Auckland University of Technology, New Zealand, M. S. Mehmood, M. Imran, Sajid Brothers Engineering Industries, Gujranwala, Pakistan, Ministry of Industries and Production, Islamabad, Pakistan
2018 Žurnal Inženernih Nauk  
To overcome these issues between the machine fault symptoms and estimating the severity of the fault; a new method of artificial intelligence fault diagnosis based approach Dempster-Shafer theory has been  ...  In this context reliability can be described as the probability that machine network will implement its proposed functions under the observing condition throughout a specified time period of running machine  ...  Acknowledgements The authors would like to thanks to Sajid Brothers Engineering Industries (Pvt.) Ltd Gujranwala Pakistan for technical support.  ... 
doi:10.21272/jes.2018.5(2).e4 fatcat:ds37ypqwszg6vp3aykpnrbaobu
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