574 Hits in 5.2 sec

Evidential Networks for Reliability Analysis and Performance Evaluation of Systems With Imprecise Knowledge

C. Simon, P. Weber
2009 IEEE Transactions on Reliability  
We apply evidential networks in reliability analysis with imprecise parameters and evaluate system performance with imprecise probabilities and utility functions.  ...  This paper deals with evidential networks to manage imprecise probabilities. We also extend utility functions to evidential networks.  ...  network as well as in a problem of modeling of imprecise reliability of a system as for the performance evaluation by imprecise utility functions.  ... 
doi:10.1109/tr.2008.2011868 fatcat:y2nlrwd3yje5pnqbpznlhnekhi

Imprecise reliability by evidential networks

C Simon, P Weber
2009 Proceedings of the Institution of Mechanical Engineers. Part O, Journal of risk and reliability  
This article deals with an implementation of probist reliability problems in evidential networks to propagate imprecise probabilities expressed as fuzzy numbers.  ...  The imprecise probist reliability of complex system by modelling the component failure probabilities as real, interval or fuzzy numbers is pointed out. Two numerical studies of systems are done.  ...  The goal of this paper is to propose a graphical formalism allowing to model imprecise reliability with certain and uncertain probabilities (real, interval or fuzzy probabilities) and to show how to propagate  ... 
doi:10.1243/1748006xjrr190 fatcat:jq5a3z2gafbmfoyswgqp62q3vy

Learning Decision Trees from Uncertain Data with an Evidential EM Approach

Nicolas Sutton-Charani, Sebastien Destercke, Thierry Denoeux
2013 2013 12th International Conference on Machine Learning and Applications  
Some promising experiments compare the obtained trees with classical CART decision trees.  ...  We therefore need a flexible and generic enough model to represent and treat this uncertainty, such as belief functions.  ...  ACKNOWLEDGEMENT The authors would like to greatly thank Brigitte Charnomordic and Nicolas Verzelen from the UMR MISTEA for their precious help and all their valuable and useful remarks and advices.  ... 
doi:10.1109/icmla.2013.26 dblp:conf/icmla/Sutton-CharaniDD13 fatcat:gq6r57pnnbgjbmvr2d7kbq2rfa

Evidence fusion with contextual discounting for multi-modality medical image segmentation [article]

Ling Huang, Thierry Denoeux, Pierre Vera, Su Ruan
2022 arXiv   pre-print
The framework is composed of an encoder-decoder feature extraction module, an evidential segmentation module that computes a belief function at each voxel for each modality, and a multi-modality evidence  ...  As information sources are usually imperfect, it is necessary to take into account their reliability in multi-source information fusion tasks.  ...  The evidence from the T1 modality is less reliable for the three classes compared to the evidence of the other three modalities.  ... 
arXiv:2206.11739v2 fatcat:e6yfaxot2ngftafuqvd4thmyje

A decision support system using multi-source scientific data, an ontological approach and soft computing - application to eco-efficient biorefinery

Lousteau-Cazalet Charlotte, Barakat Abdellatif, Belaud Jean-Pierre, Buche Patrice, Busset Guillaume, Charnomordic Brigitte, Dervaux Stephane, Destercke Sebastien, Dibie Juliette, Sablayrolles Caroline, Vialle Claire
2016 2016 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)  
Imprecision and uncertainty can arise from data incompleteness and variability. This is particularly true for processes involving biological materials. Document reliability should also be considered.  ...  and visualize indicators taking into account data imprecision.  ...  Moreover a model has been used to assess the reliability of data source, and a ranking of results is done taking into account data imprecision and reliability.  ... 
doi:10.1109/fuzz-ieee.2016.7737694 dblp:conf/fuzzIEEE/Lousteau-Cazalet16 fatcat:4rusl2tzvbfnncp5vu5mewptve

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).  ...  A small system is used to compare the reliability estimations obtained by the proposed DEN model and those obtained by the classical Markov Chain.  ...  The propagation through the Dynamic Evidential Network model allows taking into account the dependency between the failure modes for the computation of the system reliability R(k).  ... 
doi:10.1109/med.2008.4602011 fatcat:qt5cs32fbbhj5mt2ac7iiaii5m

Evidential-EM Algorithm Applied to Progressively Censored Observations [chapter]

Kuang Zhou, Arnaud Martin, Quan Pan
2014 Communications in Computer and Information Science  
Evidential-EM (E2M) algorithm is an effective approach for computing maximum likelihood estimations under finite mixture models, especially when there is uncertain information about data.  ...  The prior uncertain information is expressed by belief functions, while the pseudo-likelihood function is derived based on imprecise observations and prior knowledge.  ...  The censored data provide some kind of imprecise information for reliability analysis. It is interesting to evaluate the reliability performance for items with mixture distributions.  ... 
doi:10.1007/978-3-319-08852-5_19 fatcat:2ls5ageq6bbajitzz3dg2m2py4

Deep PET/CT fusion with Dempster-Shafer theory for lymphoma segmentation [article]

Ling Huang, Thierry Denoeux, David Tonnelet, Pierre Decazes, Su Ruan
2021 arXiv   pre-print
In this paper, we propose an lymphoma segmentation model using an UNet with an evidential PET/CT fusion layer.  ...  We evaluate our proposal on a database of polycentric PET/CT volumes of patients treated for lymphoma, delineated by the experts.  ...  or imprecise information.  ... 
arXiv:2108.05422v1 fatcat:7omwlrnnjnhzvlfgpmqpr4j5ha

Technical Gestures Recognition by Set-Valued Hidden Markov Models with Prior Knowledge [chapter]

Yann Soullard, Alessandro Antonucci, Sébastien Destercke
2016 Advances in Intelligent Systems and Computing  
Hidden Markov models are popular tools for gesture recognition.  ...  By modelling such imbalances as a prior information, we achieve more accurate results, while the imprecise quantification is shown to produce more reliable estimates.  ...  Hidden Markov Models (HMMs, [9] ) are probabilistic graphical models that can easily cope with multivariate time series, and are therefore often used for gesture recognition [2, 6] .  ... 
doi:10.1007/978-3-319-42972-4_56 fatcat:mfm7psw7jfhtvn6eiy5t7umo6m

A two-step fusion process for multi-criteria decision applied to natural hazards in mountains [article]

Jean-Marc Tacnet, Jean Dezert
2010 arXiv   pre-print
Expertise is considered as a decision process based on imperfect information coming from more or less reliable and conflicting sources.  ...  Knowledge about natural phenomenona is often lacking and expertise is required for decision and risk management purposes using multi-disciplinary quantitative or qualitative approaches.  ...  DSmT proposes more valuable modeling principles for vague, imprecise and uncertain information and conflict management.  ... 
arXiv:1005.0896v1 fatcat:d2zxyerqpzbazlaslqyfukb5d4

A Two-Step Fusion Process For Multi-Criteria Decision Applied To Natural Hazards In Mountains

Jean-Marc Tacnet, Mireille Batton-Hubert, Jean Dezert
2010 Zenodo  
Expertise is considered as a decision process based on imperfect information coming from more or less reliable and conflicting sources.  ...  Knowledge about natural phenomenona is often lacking and expertise is required for decision and risk management purposes using multi-disciplinary quantitative or qualitative approaches.  ...  DSmT proposes more valuable modeling principles for vague, imprecise and uncertain information and conflict management.  ... 
doi:10.5281/zenodo.32206 fatcat:2ez63kxozvgxdggorfxsieoway

Evaluating Data Reliability: An Evidential Answer with Application to a Web-Enabled Data Warehouse

S. Destercke, P. Buche, B. Charnomordic
2013 IEEE Transactions on Knowledge and Data Engineering  
There are many available methods to integrate information source reliability in an uncertainty representation, but there are only a few works focusing on the problem of evaluating this reliability.  ...  However, data reliability and confidence are essential components of a data warehousing system, as they influence subsequent retrieval and analysis.  ...  or graphics.  ... 
doi:10.1109/tkde.2011.179 fatcat:aq7rnj2cl5h5vbrzamnmpoqfja

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

C. Simon, P. Weber, A. Evsukoff
2008 Reliability Engineering & System Safety  
The basic concepts of the Bayesian networks application to reliability analysis are introduced and a model to compute the reliability for the case study is presented.  ...  The reliability analysis problem is described and the usual methods for quantitative reliability analysis are presented within a case study.  ...  The upper and lower bounds of a probability model an imprecision on the value of the failure probability.  ... 
doi:10.1016/j.ress.2007.03.012 fatcat:dvklyp7quzch7jtkpc77d5atf4

A Belief Rule Based Flood Risk Assessment Expert System using Real Time Sensor Data Streaming

Ahmed Afif Monrat, Raihan Ul Islam, Mohammad Shahadat Hossain, Karl Andersson
2018 2018 IEEE 43rd Conference on Local Computer Networks Workshops (LCN Workshops)  
Since the integrated BRBES employs knowledge driven learning mechanism, it has been compared with other data-driven learning mechanisms to determine the reliability in assessing flood risk.  ...  Data for the expert system has been collected by considering different case study areas of Bangladesh to validate the system.  ...  A comprehensive study with performance evaluation has been performed to demonstrate how knowledge driven approach (BRBES) is performing compare to other data driven model, for example ANN, linear regression  ... 
doi:10.1109/lcnw.2018.8628607 dblp:conf/lcn/MonratIHA18 fatcat:istoy7wmoba25hnfrhueoaeode

The Belief Noisy-OR Model Applied to Network Reliability Analysis

Kuang Zhou, Arnaud Martin, Quan Pan
2016 International Journal of Uncertainty Fuzziness and Knowledge-Based Systems  
The application of BNOR model on the reliability evaluation problem of networked systems demonstrates its effectiveness.  ...  Compared with NOR, more rich information which is of great value for making decisions can be got when the available knowledge is uncertain.  ...  The concept of evidential networks, which is a combination of belief function theory and Bayesian network, is proposed to model system reliability with imprecise knowledge 25;26 .  ... 
doi:10.1142/s0218488516500434 fatcat:stvr3hcyofe75pdjvcurvtl6yy
« Previous Showing results 1 — 15 out of 574 results