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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.  ...  First, the problem of imprecise knowledge in reliability problems is described concerning system and data reprsentation.  ...  a variable can be coded by a set of basic mass assignments. 4 Evidential networks to model reliability In complex system models for their reliability analysis, the variables, which represent the system  ... 
doi:10.1243/1748006xjrr190 fatcat:jq5a3z2gafbmfoyswgqp62q3vy

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.  ...  Therefore, such imprecision and uncertainty need to be taken into account in reliability analysis.  ...  Evidential Networks for Fault Tree Analysis FTA is a logical and diagrammatic method to evaluate the probability of an accident resulting from sequences and combinations of faults and failure events in  ... 
doi:10.1515/tjj-2012-0015 fatcat:frxweofz7zci5k554bj7swisbm

Subject index to volume 2

1988 International Journal of Approximate Reasoning  
, construction of, 337 Bayes' rule of conditioning, 328 Bayesian analysis, decision tree induction system and, 330 Bayesian approach, heuristic, to knowledge acquisition, application to analysis of tissuetype  ...  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  ...  systems, 273-278 Knowledge networks, combined and adaptive, hidden patterns in, 377-393 Learning concepts, logical aspects of, 349-364 in knowledge-based systems, with imperfect teacher, 111-112  ... 
doi:10.1016/0888-613x(88)90114-4 fatcat:rj373wy2pzff3d3otqdhxs2gca

A Belief Rule Based Expert System for Evaluating Technological Innovation Capability of High-Tech Firms Under Uncertainty

Mohammad Newaj Jamil, Mohammad Shahadat Hossain, Raihan ul Islam, Karl Andersson
2019 2019 Joint 8th International Conference on Informatics, Electronics & Vision (ICIEV) and 2019 3rd International Conference on Imaging, Vision & Pattern Recognition (icIVPR)  
However, a comparison between the knowledge-driven approach (BRBES) and several data-driven models has been performed to find out the reliability in evaluating TIC.  ...  In order to evaluate TIC in a reliable way, a Belief Rule Base (BRB) Expert System can be used to handle both quantitative and qualitative data and their associated uncertainties.  ...  BRB expert system uses Belief Rule Base (BRB) for representing uncertain knowledge and creating the initial knowledge base, while Evidential Reasoning (ER) works as an inference engine to handle heterogeneous  ... 
doi:10.1109/iciev.2019.8858550 fatcat:3hqwjibptfevpe2tr6gkafu7oe

Fault Diagnosis of Power Transformers Using Computational Intelligence: A Review

Huo-Ching Sun, Yann-Chang Huang, Chao-Ming Huang
2012 Energy Procedia  
This study reviews computational intelligence (CI) approaches for oil-immersed power transformer maintenance by discussing historical developments and by presenting state-of-the-art fault diagnosis methods  ...  The CI-based approaches have emerged as rapidly evolving but highly effective approaches for using dissolved gas analysis (DGA) data for diagnosing power transformer faults.  ...  The grey theory combines clustering analysis, relational analysis, prediction, and grey system decision making.  ... 
doi:10.1016/j.egypro.2011.12.1080 fatcat:2mn5p5hhvfg5zehcnkiyezumuy

Page 7122 of Mathematical Reviews Vol. , Issue 97K [page]

1997 Mathematical Reviews  
This paper deals with the relationship between evidential structures of Dempster-Shafer theory and the data table based knowledge representation systems subject to rough set analysis.  ...  Summary: “We present an extension of Bayesian networks to prob- ability intervals, aiming at a more realistic and flexible modeling of applications with uncertain and imprecise knowledge.  ... 

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.  ...  BNOR is capable of dealing with both aleatory and epistemic uncertainty of the network.  ...  This work was supported by the National Natural Science Foundation of China (Nos.61135001, 61403310). The study of the first author in France was supported by the China Scholarship Council.  ... 
doi:10.1142/s0218488516500434 fatcat:stvr3hcyofe75pdjvcurvtl6yy

A novel failure mode and effects analysis method based on fuzzy evidential reasoning rules

Wen Jiang, Zhipeng Zhang, Xinyang Deng
2019 IEEE Access  
Failure mode and effects analysis (FMEA) is an effective reliability analysis technique and has been used for safety and dependability analysis in a wide range of fields.  ...  However, the method is deficient in dealing with imprecise data.  ...  However, because of the increasing complexity of system and the lack of knowledge, they may be not easy to be precisely evaluated in the real situation.  ... 
doi:10.1109/access.2019.2934495 fatcat:e5ahaxht75gp5lrfiwnegh4ijm

The belief noisy-or model applied to network reliability analysis [article]

Kuang Zhou, Quan Pan
2016 arXiv   pre-print
The application of BNOR model on the reliability evaluation problem of networked systems demonstrates its effectiveness.  ...  BNOR is capable of dealing with both aleatory and epistemic uncertainty of the network.  ...  This work was supported by the National Natural Science Foundation of China (Nos.61135001, 61403310). The study of the first author in France was supported by the China Scholarship Council.  ... 
arXiv:1606.01116v1 fatcat:ehjashmhsje2tbqdhup3ha77bu

Augmenting Deep Learning Performance in an Evidential Multiple Classifier System

Jennifer Vandoni, Sylvie Le Hégarat-Mascle, Emanuel Aldea
2019 Sensors  
We show that the fusion resulting from the effective modeling of uncertainty allows for performance improvement, and at the same time, for a deeper interpretation of the result in terms of commitment of  ...  and intrinsic imprecision of annotation data.  ...  and derive evidential measures of imprecision.  ... 
doi:10.3390/s19214664 pmid:31717870 pmcid:PMC6864766 fatcat:hnwjfpvnpbh6rptt62zoe4ekdi

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)  
Data for the expert system has been collected by considering different case study areas of Bangladesh to validate the system.  ...  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.  ...  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

An Intelligent System to Diagnose Chikungunya under Uncertainty

Mohammad Shahadat Hossain, Zinnia Sultana, Lutfun Nahar, Karl Andersson
2019 Journal of Wireless Mobile Networks, Ubiquitous Computing, and Dependable Applications  
A comparison has been performed with the results of BRBES and Fuzzy Logic Based Expert System (FLBES) as well as with the expert judgment.  ...  Furthermore, the result of BRBES has been contrasted with various data-driven machine learning approaches, including ANN (Artificial Neural networks) and SVM (Support Vector Machine).  ...  The reason for the better performance of BRBES is that it considers different categories of uncertainty linked with the signs and symptoms of Chikungunya.  ... 
doi:10.22667/jowua.2019.06.30.037 dblp:journals/jowua/HossainSNA19 fatcat:ynjycjsk4zhsbb7dhwpgnubmne

Sensitivity Analysis for Systems under Epistemic Uncertainty with Probability Bounds Analysis

Geng Feng
2018 International Journal of Computer Applications  
In this paper, survival signature is adopted to evaluate the system performance, and the area value of the probability box is introduced to reflect the epistemic uncertainty of the system.  ...  System sensitivity analysis provides a quantitative tool for accessing the importance of components within a specific system configuration.  ...  Evidential networks for reliability analysis and performance evaluation of systems with imprecise knowledge was introduced by Simon and Weber [28] .  ... 
doi:10.5120/ijca2018915892 fatcat:xyujxzb2nfbahe7w54ma5dym6e

Improving Driver Assistance in Intelligent Transportation Systems: An Agent-Based Evidential Reasoning Approach

M. Benalla, B. Achchab, H. Hrimech
2020 Journal of Advanced Transportation  
In order to improve the knowledge base of advanced driver assistance systems (ADAS), ITS are strongly concerned with data fusion techniques of all kinds of sensors deployed over the traffic network.  ...  A case study including various scenarios of experiments is introduced to estimate behavioral information based on synthetic data for prediction, prescription, and policy analysis.  ...  Acknowledgments e first author is grateful for the support provided by the "Centre National pour la Recherche Scientifique et Technique (CNRST)" of Morocco, under contract no. K005/006.  ... 
doi:10.1155/2020/4607858 fatcat:vv7uhahm7vawjflntdo62nuxny
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