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Classification of Message Spreading in a Heterogeneous Social Network [chapter]

Siwar Jendoubi, Arnaud Martin, Ludovic Liétard, Boutheina Ben Yaghlane
2014 Communications in Computer and Information Science  
The goal of our paper is to classify the social message based on its spreading in the network and the theory of belief functions.  ...  In fact, they introduced new habits, new ways of communication and they collect every day several information that have different sources.  ...  This new algorithm takes four different inputs which are the number of iterations (stopping condition), the source of the message, the propagation strategy and the heterogeneous social network.  ... 
doi:10.1007/978-3-319-08855-6_8 fatcat:k24to3ogr5evzhf2x47ml3ugji

Prioritization Assessment for Capability Gaps in Weapon System of Systems Based on the Conditional Evidential Network

Dong Pei, Daguo Qin, Yang Sun, Guangzhi Bu, Zhonghua Yao
2018 Applied Sciences  
Later, in 2013, they proposed a new propagation algorithm for a dynamic directed evidence network with conditional belief functions, based on a new computational structure called Mixed Binary Tree [21]  ...  In 2012, Wafa and Yaghlane used a dynamically-directed evidential network with conditional belief functions for a study on system reliability, indicating that the directed evidential network is moving  ...  Author Contributions: Dong Pei and Daguo Qin conceived and designed the evidential network model; Dong Pei studied the case, Yang Sun, Guangzhi Bu, and Zhonghua Yao helped in the case study; Dong Pei analyzed  ... 
doi:10.3390/app8020265 fatcat:rxtig5qalvbvld4a5sum2izq4m

Time-Sliced Temporal Evidential Networks: The case of Evidential HMM with application to dynamical system analysis

Lisa Serir, Emmanuel Ramasso, Noureddine Zerhouni
2011 2011 IEEE Conference on Prognostics and Health Management  
The generalization of this training procedure to more general Time-Sliced Temporal Evidential Network (TSTEN) is discussed paving the way for a further generalization of Dynamic Bayesian Network to belief  ...  In this paper, we propose to complete the generalization of HMM to belief functions with a method for automatic parameter training.  ...  The proposed methodology is adapted with poor training sets and more experiments are under way to thoroughly validate the approach for general diagnostics and prognostics tasks.  ... 
doi:10.1109/icphm.2011.6024330 fatcat:3c5nfgotf5ah5cnxo6xke5uhc4

A new uncertainty measure for belief networks with applications to optimal evidential inferencing

Jiming Liu, D.A. Maluf, M.C. Desmarais
2001 IEEE Transactions on Knowledge and Data Engineering  
AbstractÐThis paper is concerned with the problem of measuring the uncertainty in a broad class of belief networks, as encountered in evidential reasoning applications.  ...  We demonstrate, with Monte Carlo simulation, the implementation and the effectiveness of the proposed dynamical observer in solving the problem of evidential inferencing with optimal evidence node selection  ...  Some belief networks decompose the joint-probability distribution of real-world probabilistic knowledge with conditionals [16] , while others focus on the belief-function measures of the nodes as supported  ... 
doi:10.1109/69.929899 fatcat:et63jac7qfarjjgb3sxpjdlybm

Evidential Networks for Evaluating Predictive Reliability of Mechatronics Systems under Epistemic Uncertainties

Nabil B. Amrani, Laurent Saintis, Driss Sarsri, Mihaela Barreau
2019 Journal of KONBiN  
The key point in this study is to use an Evidential Network "EN" based on belief functions and the dynamic Bayesian network.  ...  complex systems with high-reliability precision such as mechatronic systems, uncertainties are inevitable and must be considered in order to predict with a degree of confidence the evaluated reliability  ...  belief propagation (NBP) algorithm.  ... 
doi:10.2478/jok-2019-0045 fatcat:cghfor65avgndmitzjftywo5i4

Decision-Support Methodology to Assess Risk in End-of-Life Management of Complex Systems

Eric Villeneuve, Cedrick Beler, Francois Peres, Laurent Geneste, Eric Reubrez
2017 IEEE Systems Journal  
Index Terms-Belief functions, decision-support system, directed evidential networks, end-of-life management, risk assessment.  ...  The theory of belief functions provides a common framework to facilitate fusion of multisource knowledge, and a directed evidential network is used to compute a measure of the risk level.  ...  This formalism is similar to Bayesian networks [2] but uses conditional belief functions instead of conditional probabilities.  ... 
doi:10.1109/jsyst.2016.2522183 fatcat:lnd4sln54zaktldjfemmswxloe

Dynamic evidential networks in system reliability analysis: A Dempster Shafer approach

Philippe Weber, Christophe Simon
2008 2008 16th Mediterranean Conference on Control and Automation  
To address these difficulties, this paper presents a new method for modeling and analyzing the system reliability based on Dynamic Evidential Networks (DEN).  ...  Moreover the results computed with classical methods need to be reinforced by managing the uncertainty.  ...  Dynamic Evidential Network A Dynamic Evidential Network is an EN including a temporal dimension. This new dimension is managed by time-indexed variables.  ... 
doi:10.1109/med.2008.4602011 fatcat:qt5cs32fbbhj5mt2ac7iiaii5m

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.  ...  Figure 6 . 6 Bridge system reliability model with the Evidential Network. C 1 . 1 The propagation of this uncertainty can be observed in the Bayesian Network.  ... 
doi:10.4304/jcp.2.1.33-43 fatcat:qg2n7imvkbgh5o3pneuywdwxcm

Discovery and Use of Causal Patterns in Databases

D. Bell, F. McErlean, J. Guan
2000 Journal of Intelligent Systems  
In our method a number of models are obtained from a variety of algorithms.  ...  KEYWORDS knowledge discovery in databases, data mining, automated reasoning, causality, evidential causal updating, decision trees f We are sad to report that Francis McElean died in November 1998.  ...  The second part of this paper deals with the use of these networks in evidential reasoning. The central concept in this part is belief propagation.  ... 
doi:10.1515/jisys.2000.10.2.109 fatcat:oevcs2wusrbztgxemglco5jevm

Automatic Updates of Transition Potential Matrices in Dempster-Shafer Networks Based on Evidence Inputs

Joel Dunham, Eric Johnson, Eric Feron, Brian German
2020 Sensors  
Together, these methods enable updating a Dempster-Shafer network with significantly less user input, thereby making these networks more useful for scenarios in which sufficient information concerning  ...  Novel refinements to the method are also introduced, demonstrating improvements in capturing the relationships between the node belief distributions.  ...  Acknowledgments: The authors are thankful to Olivia Jagiella-Lodise for her contributions in editing this paper. Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/s20133727 pmid:32635275 pmcid:PMC7374387 fatcat:zjdb2q3wwjhg5o36mwycysd3pu

Evidential Networks for Fault Tree Analysis with Imprecise Knowledge

Jianping Yang, Hong-Zhong Huang, Yu Liu, Yan-Feng Li
2012 International journal of turbo & jet-engines  
In this paper, the evidential networks (EN) are employed to quantify and propagate the aforementioned uncertainty and imprecision in fault tree analysis.  ...  The figures of the logic gates and the converted equivalent EN, together with the associated truth tables and the conditional belief mass tables, are also presented in this work.  ...  Evidential networks can deal with aleatory and epistemic uncertainties in reliability engineering. Consequently, the conversion algorithm from FT to evidential networks should be detailed.  ... 
doi:10.1515/tjj-2012-0015 fatcat:frxweofz7zci5k554bj7swisbm

Knowledge Acquisition, Representation & Manipulation in Decision Support Systems [article]

M.Michalewicz, S.T.Wierzchoń, M.A. Kłopotek
2017 arXiv   pre-print
Further a concept of an interface to probabilistic and DS belief networks enabling a user to understand the communication with a belief network based reasoning system is presented  ...  Next we show some aspects of belief network approach and Dempster-Shafer (DST) methodology introduced in practice to system SEAD.  ...  This fully justifies, in our opinion, the usage of the new belief network definition. Understanding a Belief Network in Terms of Rules A dag structure of a belief network was presented in Fig.1 .  ... 
arXiv:1705.08440v1 fatcat:4j7gbcue4rdftcku3ycq2t6zai

Approximate Evidential Reasoning Using Local Conditioning and Conditional Belief Functions

Van Nguyen
2017 Conference on Uncertainty in Artificial Intelligence  
We propose a new message-passing belief propagation method that approximates belief updating on evidential networks with conditional belief functions.  ...  By means of local conditioning, the method is able to propagate beliefs on the original multiply-connected network structure using local computations, facilitating reasoning in a distributed and dynamic  ...  In Section 4, we present our new approximate belief updating method that combines local conditioning with conditional belief functions.  ... 
dblp:conf/uai/Nguyen17 fatcat:jgtv6ajpijaabogmje2gmi5cv4

An Application of Evidential Networks to Threat Assessment

A. Benavoli, B. Ristic, A. Farina, M. Oxenham, L. Chisci
2009 IEEE Transactions on Aerospace and Electronic Systems  
To reduce computational overheads, the scheme performs local computations in the network by applying an inward propagation algorithm to the underlying binary join tree.  ...  Threat is modelled by a network of entities and relationships between them, while the uncertainties in the relationships are represented by belief functions as defined in the theory of evidence.  ...  BELIEF FUNCTIONS AS VALUATIONS A VBS with valuations expressed by belief functions (as defined in the theory of evidence) will be referred to as an evidential network. if H = Θ h and zero otherwise.  ... 
doi:10.1109/taes.2009.5089545 fatcat:pcif5bn6h5cptahcr3heqbecjq

A Constraint Propagation Approach to Probabilistic Reasoning [article]

Judea Pearl
2013 arXiv   pre-print
Maintaining local records of sources-of-belief allows both predictive and diagnostic inferences to be activated simultaneously and propagate harmoniously towards a stable equilibrium.  ...  The paper demonstrates that strict adherence to probability theory does not preclude the use of concurrent, self-activated constraint-propagation mechanisms for managing uncertainty.  ...  in a new equilibrium state compatible with the newly observed eviden . ce.  ... 
arXiv:1304.3422v1 fatcat:euxqiaybkjdnvj4epsexbnxd2y
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