Journal ArticleDOI
Safety analysis in process facilities: Comparison of fault tree and Bayesian network approaches
TLDR
The paper concludes that BN is a superior technique in safety analysis because of its flexible structure, allowing it to fit a wide variety of accident scenarios.About:
This article is published in Reliability Engineering & System Safety.The article was published on 2011-08-01. It has received 573 citations till now. The article focuses on the topics: Fault tree analysis & System safety.read more
Citations
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Journal ArticleDOI
Risk Assessment of Seaplane Operation Safety Using Bayesian Network
TL;DR: A novel approach to modeling the risk of seaplane operation safety using a Bayesian network (BN), which shows that the four most critical risk factors are mental barrier, mechanical failure, visibility, and improper emergency disposal.
Journal ArticleDOI
Risk analysis and maintenance decision making of natural gas pipelines with external corrosion based on Bayesian network
TL;DR: In this paper , a risk analysis and maintenance decision-making model for natural gas pipelines with external corrosion is proposed based on a Bayesian network, where a fault tree model is first employed to identify the causes of external corrosion.
Journal ArticleDOI
Passive Solar Desalination Systems. Classification, Study Parameters and Future Enhancements.
TL;DR: A fuzzy Bayesian network to model and analyze risk in the operating room and provides an actionable model that accurately supports human cognition using linguistic variables is proposed.
Journal ArticleDOI
Developing a comprehensive risk assessment model based on fuzzy Bayesian belief network (FBBN)
TL;DR: The comparison shows that the proposed risk assessment model is able to provide guidelines for an effective risk management process and ultimately to increase project performance in a complex environment such as international construction projects.
Journal ArticleDOI
Establishment of safety structure theory
TL;DR: SST is a new safety science theory, which can provide a new analysis method for revealing the essence of “safety” and the evolution mechanism of safety issues, and open up a new way for the development of active safety control.
References
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Book
Bayesian networks and decision graphs
TL;DR: The book introduces probabilistic graphical models and decision graphs, including Bayesian networks and influence diagrams, and presents a thorough introduction to state-of-the-art solution and analysis algorithms.
Journal ArticleDOI
Improving the analysis of dependable systems by mapping fault trees into Bayesian networks
TL;DR: It is shown that any FT can be directly mapped into a BN and that basic inference techniques on the latter may be used to obtain classical parameters computed from the former, i.e. reliability of the Top Event or of any sub-system, criticality of components, etc.
Book
Introduction to reliability engineering
TL;DR: Reliability and Rates of Failure, Loads, Capacity, and Reliability, and System Safety Analysis; Quality and Its Measures; and Answers to Odd--Numbered Exercises.
Journal ArticleDOI
Overview on Bayesian networks applications for dependability, risk analysis and maintenance areas
TL;DR: A bibliographical review over the last decade is presented on the application of Bayesian networks to dependability, risk analysis and maintenance and an increasing trend of the literature related to these domains is shown.
Book
Bayesian Networks and Influence Diagrams: A Guide to Construction and Analysis
Uffe Kjærulff,Anders L. Madsen +1 more
TL;DR: Bayesian Networks and Influence Diagrams: A Guide to Construction and Analysis provides a comprehensive guide for practitioners who wish to understand, construct, and analyze intelligent systems for decision support based on probabilistic networks.