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Decision Support Software for Probabilistic Risk Assessment Using Bayesian Networks
2014
IEEE Software
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These are the types of situation that can be successfully addressed using Bayesian Networks (BNs) [2] , even when data-driven approaches to risk assessment are not possible. ...
BNs (see Fig 1) describe "webs" of causes and effects, using a graphical framework that provides for the rigorous quantification of risks and the clear communication of results. ...
This means that the vast majority of business users continue to rely on decision support and risk assessment tools that do not provide the power, accuracy and insights of BN solutions. ...
doi:10.1109/ms.2014.32
fatcat:kpg4ppwy5rbp7pnl3upucirusa
A BOW-TIE BASED RISK FRAMEWORK INTEGRATED WITH A BAYESIAN BELIEF NETWORK APPLIED TO THE PROBABILISTIC RISK ANALYSIS
2015
Brazilian Journal of Operations & Production Management
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To remedy this problem, the methodology presented in this paper covers the construction of a probabilistic risk analysis model, based on Bayesian Belief Network coupled to a bow-tie diagram. ...
The use of probabilistic risk analysis in the jet engines manufacturing process is essential to prevent failure. ...
A Bayesian network software is used to run the model, the probability values obtained for the nodes are also shown in the Figure 8. ...
doi:10.14488/bjopm.2015.v12.n2.a14
fatcat:ou6k7ovrpnchfgvt6fp54bbiqy
Risk Prediction for Production of an Enterprise
2013
International Journal of Computer Applications Technology and Research
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For this, Multi-Entity Bayesian Network (MEBN) has been used to represent the requirements for production management as well as to assess the risks adherence in production management, where MEBN combines ...
Bayesian network provides the feature to represent the probabilistic uncertainty and reasoning about probabilistic knowledge base, which is used here to represent the probable risks behind each causes ...
Paulo Cesar G. da Costa for giving permissions to use any contents from their Ph. D. theses and papers. ...
doi:10.7753/ijcatr0203.1006
fatcat:t7jh5olbijdnti6ocjvzibakwu
Probabilistic risk analysis in manufacturing situational operation: application of modelling techniques and causal structure to improve safety performance
2015
International Journal of Production Management and Engineering
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Bayesian Belief Network coupled to a Bow Tie diagram is used to identify potential engine failure scenarios. ...
As a result of this study, this paper presents a model that combines fault tree analysis, event tree analysis and a Bayesian Belief Networks into a single model that can be used by decision makers to identify ...
The Bayesian network software named Agena Risk is used to run the model, the probability values obtained for the nodes are also shown in the Figure 8 . ...
doi:10.4995/ijpme.2015.3287
fatcat:vrhapqjhivgftdlbx4iksinimu
A Survey of Bayesian Network Models for Decision Making System in Software Engineering
2016
International Journal of Computer Applications
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This model reveals the high potential software efforts and metrics required to minimize the overall cost of the organization for decision support. ...
Bayesian networks are applied to find the probabilistic relationships among the software metrics in different phases of software life cycle. ...
INTRODUCTION Over the last few years, Bayesian networks have become widely used in probabilistic models to predict the defect or quality analysis of software development to reduce human resources as well ...
doi:10.5120/ijca2016906330
fatcat:cq45rwqsubaadfwszki26bap6q
'This is what we don't know' ‐ Treating epistemic uncertainty in Bayesian networks for risk assessment
2020
Integrated Environmental Assessment and Management
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EDITOR'S NOTE: This article is part of the special series "Applications of Bayesian Networks for Environmental Risk Assessment and Management" and was generated from a session on the use of Bayesian networks ...
Failing to communicate current knowledge limitations, i.e. epistemic uncertainty, in environmental risk assessment (ERA) may have severe consequences for decision-making. ...
Besides, to encourage the use of BNs in risk assessments, efforts to extend existing software packages to support enhanced BNs and probabilistic uncertainty analysis for aleatory BNs would be beneficial ...
doi:10.1002/ieam.4367
pmid:33151017
fatcat:utksecqtlbbz5c7ep2sxoisv4m
A Probabilistic Software Risk Assessment and Estimation Model for Software Projects
2015
Procedia Computer Science
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In this paper, a probabilistic software risk estimation model is proposed using Bayesian Belief Network (BBN) that focuses on the top software risk indicators for risk assessment in software development ...
In order to assess the constructed model, an empirical experiment has been performed, based on the data collected from software development projects used by an organization. ...
In this paper, a model is proposed for software risk assessment using the top ranked software risk indicator 9 . ...
doi:10.1016/j.procs.2015.06.041
fatcat:ymlo5fv6qfcnflubgynv6pavt4
Simulation-based Probabilistic Risk Assessment
[article]
2022
arXiv
pre-print
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In this regard, multiple statistical and probabilistic tools can be used to provide a valuable assessment of dynamic probabilistic risk levels in different applications. ...
Simulation-based probabilistic risk assessment (SPRA) is a systematic and comprehensive methodology that has been used and refined over the past few decades to evaluate the risks associated with complex ...
[26] proposed a methodology which leveraged simulation, dynamic probabilistic risk assessment, and dynamic Bayesian networks to provide real-time diagnostic and monitoring for severe accidents in a ...
arXiv:2207.12575v1
fatcat:br3xhpihazaz7hcm2w7ozriivm
Probabilistic Assessment of Road Risks for Improving Logistics Processes
2018
MATEC Web of Conferences
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To identify this last problem of road risk and to minimize its influence, a Bayesian network has been developed in this paper. ...
Through experts' surveys and research in the literature, the various risks were identified. The structure of the Bayesian network is defined on the basis of this census. ...
In this article, Netica software [10] is used to build an analysis and road risk assessment model to anticipate failures in the logistics function. ...
doi:10.1051/matecconf/201818301003
fatcat:5igd4diq25e5zkp5huz276tcom
An Ontology Driven and Bayesian Network Based Cardiovascular Decision Support Framework
[chapter]
2012
Lecture Notes in Computer Science
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Keywords: cardiovascular decision support system, ontology driven decision support with uncertainty modeling, clinical decision support and Bayesian Network. ...
In this paper, we present a cardiovascular decision support framework based on key ontology engineering principles and a Bayesian Network. ...
Bayesian Networks Bayesian Networks hold an important position in modern clinical decision support systems. ...
doi:10.1007/978-3-642-31561-9_4
fatcat:5xbsi5mryveddlxi7gzyck3ygy
Bayesian Networks for Decision-Making and Causal Analysis under Uncertainty in Aviation
[chapter]
2018
Bayesian Networks [Working Title]
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The chapter addresses the three main ways in which Bayesian networks are currently employed for scientific or regulatory decisionmaking purposes in the aviation industry, depending on the extent to which ...
This chapter illustrates how Bayesian analysis can constitute a systematic approach for dealing with uncertainties in aviation and air transport. ...
Bayesian networks for decision-making in aviation In general, we may consider three main ways that Bayesian networks are currently employed in causal and risk analysis for scientific or regulatory decision-making ...
doi:10.5772/intechopen.79916
fatcat:fuu2frhfvfe3bkditzojaugw7u
Development of a Bayesian network for probabilistic risk assessment of pesticides
[article]
2021
bioRxiv
pre-print
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In this study, a probabilistic approach using Bayesian network (BN) modelling is explored as an alternative to traditional risk calculation. ...
Probabilistic risk assessment approaches can offer more transparency, by using probability distributions for exposure and/or effects to account for variability and uncertainty. ...
Probabilistic risk assessment using Bayesian networks The early efforts of probabilistic risk assessment for pesticides, which were usually visualised by cumulative distribution curves, were sometimes ...
doi:10.1101/2021.05.20.444913
fatcat:oatc76wiwzbtxabpuupfmx6fua
Cognitive Identity Management: Risks, Trust and Decisions using Heterogeneous Sources
2019
2019 IEEE First International Conference on Cognitive Machine Intelligence (CogMI)
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This work advocates for cognitive biometric-enabled systems that integrate identity management, risk assessment and trust assessment. ...
The cognitive identity management process is viewed as a multi-state dynamical system, and probabilistic reasoning is used for modeling of this process. ...
Eastwood is acknowledged as a developer of the initial version of the multimetric inference software DS-BN v02. ...
doi:10.1109/cogmi48466.2019.00014
dblp:conf/cogmi/YanushkevichHCO19
fatcat:x3dkzauivrdhfakby64sjdfg6i
Development of a Bayesian network for probabilistic risk assessment of pesticides
2021
Integrated Environmental Assessment and Management
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In this study, a probabilistic approach using Bayesian network modelling is explored as an alternative to traditional risk calculation. ...
Probabilistic risk assessment approaches can offer more transparency, by using probability distributions for exposure and/or effects to account for variability and uncertainty. ...
Manag 2021:1-16 © 2021 The Authors DOI: 10.1002/ieam.4533 PROBABILISTIC RISK ASSESSMENT USING A BAYESIAN NETWORK MODEL-Integr Environ Assess Manag 00, 2021
PROBABILISTIC RISK ASSESSMENT USING A BAYESIAN ...
doi:10.1002/ieam.4533
pmid:34618406
fatcat:rfujkm62grc5tlmtwqpe53ksgi
Increased Use of Bayesian Network Models has Improved Environmental Risk Assessments
2020
Integrated Environmental Assessment and Management
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Bayesian network (BN) models are a tool for probabilistic and causal modelling, increasingly used in many fields of environmental science. ...
In conclusion, this special series supports the prediction that increased use of Bayesian network models will improve environmental risk assessments. This article is protected by copyright. ...
We are grateful to Wayne Landis for his support as the handling Senior Editor of this special series, and for inspiration and interesting discussions on the use of Bayesian networks. ...
doi:10.1002/ieam.4369
pmid:33205856
pmcid:PMC8573810
fatcat:btfqijyrw5g5nj3g73wl2fmqhe
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