FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2765767062> ?p ?o ?g. }

• W2765767062 endingPage "225" @default.
• W2765767062 startingPage "211" @default.
• W2765767062 abstract "Bayesian Network (BN) is often criticized for demanding a large number of crisp/exact/precise conditional probability numbers which, due to the lack of statistics, have to be obtained through experts’ judgment. These exact probability numbers provided by the experts often carry a high level of epistemic uncertainty due to the incompleteness of human knowledge, not to mention the hardness in obtaining them in the first place. The existence of uncertainty in risk modelling was well recognized but seldom discussed. This paper explores the extension of BN with interval probabilities to the modelling of maritime accidents, which allows for the quantification of the epistemic uncertainty. Ship collision is chosen for case study for the strategic importance of navigational safety. The user friendly linguistic terms defined with interval scales were used for elicitation of interval conditional probabilities from industry experts. Inferences were made directly with the interval probabilities with the GL2U algorithm. Meanwhile, the interval probabilities were converted into point probabilities and computed with the traditional BN method for comparison, which were all shown to be within the ranges of the calculated posterior intervals probability. Results with inputs from different experts reveal discrepancies, which in turn verify the existence of uncertainty in risk modelling. A discussion was also provided on how the uncertainty in risk assessment propagates to the decision making process and influences the ranking of potential risk control options." @default.
• W2765767062 created "2017-11-10" @default.
• W2765767062 creator A5004490474 @default.
• W2765767062 creator A5010061339 @default.
• W2765767062 creator A5013082890 @default.
• W2765767062 creator A5022255714 @default.
• W2765767062 creator A5023160938 @default.
• W2765767062 date "2018-02-01" @default.
• W2765767062 modified "2023-10-11" @default.
• W2765767062 title "Addressing the epistemic uncertainty in maritime accidents modelling using Bayesian network with interval probabilities" @default.
• W2765767062 cites W1549911417 @default.
• W2765767062 cites W1712237218 @default.
• W2765767062 cites W1967770810 @default.
• W2765767062 cites W1971668185 @default.
• W2765767062 cites W1982275833 @default.
• W2765767062 cites W1992060880 @default.
• W2765767062 cites W2004794985 @default.
• W2765767062 cites W2012105789 @default.
• W2765767062 cites W2012645710 @default.
• W2765767062 cites W2014779316 @default.
• W2765767062 cites W2021341743 @default.
• W2765767062 cites W2029510133 @default.
• W2765767062 cites W2031418630 @default.
• W2765767062 cites W2033793525 @default.
• W2765767062 cites W2042744306 @default.
• W2765767062 cites W2045759663 @default.
• W2765767062 cites W2045929226 @default.
• W2765767062 cites W2054129669 @default.
• W2765767062 cites W2056687315 @default.
• W2765767062 cites W2058547430 @default.
• W2765767062 cites W2059272990 @default.
• W2765767062 cites W2075087125 @default.
• W2765767062 cites W2076280516 @default.
• W2765767062 cites W2107243014 @default.
• W2765767062 cites W2109552086 @default.
• W2765767062 cites W2110506006 @default.
• W2765767062 cites W2122436893 @default.
• W2765767062 cites W2123517961 @default.
• W2765767062 cites W2147872046 @default.
• W2765767062 cites W2152708262 @default.
• W2765767062 cites W2153279373 @default.
• W2765767062 cites W2154728303 @default.
• W2765767062 cites W2162273094 @default.
• W2765767062 cites W2162506159 @default.
• W2765767062 cites W2305402217 @default.
• W2765767062 cites W2321991321 @default.
• W2765767062 cites W2399611375 @default.
• W2765767062 cites W2550665851 @default.
• W2765767062 cites W2913772900 @default.
• W2765767062 doi "https://doi.org/10.1016/j.ssci.2017.10.016" @default.
• W2765767062 hasPublicationYear "2018" @default.
• W2765767062 type Work @default.
• W2765767062 sameAs 2765767062 @default.
• W2765767062 citedByCount "57" @default.
• W2765767062 countsByYear W27657670622018 @default.
• W2765767062 countsByYear W27657670622019 @default.
• W2765767062 countsByYear W27657670622020 @default.
• W2765767062 countsByYear W27657670622021 @default.
• W2765767062 countsByYear W27657670622022 @default.
• W2765767062 countsByYear W27657670622023 @default.
• W2765767062 crossrefType "journal-article" @default.
• W2765767062 hasAuthorship W2765767062A5004490474 @default.
• W2765767062 hasAuthorship W2765767062A5010061339 @default.
• W2765767062 hasAuthorship W2765767062A5013082890 @default.
• W2765767062 hasAuthorship W2765767062A5022255714 @default.
• W2765767062 hasAuthorship W2765767062A5023160938 @default.
• W2765767062 hasBestOaLocation W27657670622 @default.
• W2765767062 hasConcept C105795698 @default.
• W2765767062 hasConcept C107673813 @default.
• W2765767062 hasConcept C114614502 @default.
• W2765767062 hasConcept C121117317 @default.
• W2765767062 hasConcept C12174686 @default.
• W2765767062 hasConcept C134306372 @default.
• W2765767062 hasConcept C154945302 @default.
• W2765767062 hasConcept C177803969 @default.
• W2765767062 hasConcept C189430467 @default.
• W2765767062 hasConcept C191252586 @default.
• W2765767062 hasConcept C2778067643 @default.
• W2765767062 hasConcept C32230216 @default.
• W2765767062 hasConcept C33724603 @default.
• W2765767062 hasConcept C33923547 @default.
• W2765767062 hasConcept C34388435 @default.
• W2765767062 hasConcept C38652104 @default.
• W2765767062 hasConcept C41008148 @default.
• W2765767062 hasConcept C41426520 @default.
• W2765767062 hasConcept C44492722 @default.
• W2765767062 hasConcept C49698424 @default.
• W2765767062 hasConcept C57830394 @default.
• W2765767062 hasConceptScore W2765767062C105795698 @default.
• W2765767062 hasConceptScore W2765767062C107673813 @default.
• W2765767062 hasConceptScore W2765767062C114614502 @default.
• W2765767062 hasConceptScore W2765767062C121117317 @default.
• W2765767062 hasConceptScore W2765767062C12174686 @default.
• W2765767062 hasConceptScore W2765767062C134306372 @default.
• W2765767062 hasConceptScore W2765767062C154945302 @default.
• W2765767062 hasConceptScore W2765767062C177803969 @default.
• W2765767062 hasConceptScore W2765767062C189430467 @default.
• W2765767062 hasConceptScore W2765767062C191252586 @default.

• next