FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2358903369> ?p ?o ?g. }

• W2358903369 abstract "The paper is intended to present our research results of some key accident-prone factors, such as the failure of training, the threat brought by the new products likely to cause transportation hazards yet unknown or not enough known to the airline crew members. In addition, it is also found that the fault-tree approach also has its own limitation for the hazard assessment, which pushed us to map up a fault tree of air transport of hazardous goods by putting the fault-tree information onto a Bayesian network, which includes a conditional probability distribution table for the need of assessing the system work under the inference of the Bayesian network. In doing so, we have analyzed the Bayesian network quantitatively while using the inference algorithm of Bayesian network through analyzing the data calculation. Next, we have put forward the improved measures such as ensuring the service quality of the crew members by training according to the service demands of CCAR - 276.159, ensuring the operation regulations establishment concerning the air transport of hazardous goods and improving the specific qualification system for the air Iransport of hazardous goods. Then, we have done inspections on the effectiveness of related measures with the help of Bayesian networks. Thus, it can be seen that the Bayesian network can help us to ensure a completely new hazard assessment in air transport of dangerous goods. In doing so, successful adoption of Bayesian network can greatly contribute to the effectiveness of the related improved measures, which can reduce the possibility of air transport of hazardous goods. The last but not the least is that the effectiveness of the improved measures taken helps to reduce the potential of accidents. In a word, an example on air Iransport of hazardous goods illustrates that the Bayesian network approach is a good substitute of the fault tree approach for risk assessment, and the perspective of using Bayesian network to make hazard assessment will find a wide application." @default.
• W2358903369 created "2016-06-24" @default.
• W2358903369 creator A5002847748 @default.
• W2358903369 date "2010-01-01" @default.
• W2358903369 modified "2023-09-22" @default.
• W2358903369 title "Bayesian networks analysis on the accidents of air transportation of the hazardous goods" @default.
• W2358903369 hasPublicationYear "2010" @default.
• W2358903369 type Work @default.
• W2358903369 sameAs 2358903369 @default.
• W2358903369 citedByCount "0" @default.
• W2358903369 crossrefType "journal-article" @default.
• W2358903369 hasAuthorship W2358903369A5002847748 @default.
• W2358903369 hasConcept C107094494 @default.
• W2358903369 hasConcept C107673813 @default.
• W2358903369 hasConcept C112930515 @default.
• W2358903369 hasConcept C124101348 @default.
• W2358903369 hasConcept C127313418 @default.
• W2358903369 hasConcept C127413603 @default.
• W2358903369 hasConcept C144133560 @default.
• W2358903369 hasConcept C154945302 @default.
• W2358903369 hasConcept C160234255 @default.
• W2358903369 hasConcept C162853370 @default.
• W2358903369 hasConcept C165205528 @default.
• W2358903369 hasConcept C175551986 @default.
• W2358903369 hasConcept C178790620 @default.
• W2358903369 hasConcept C178802073 @default.
• W2358903369 hasConcept C185592680 @default.
• W2358903369 hasConcept C18762648 @default.
• W2358903369 hasConcept C200601418 @default.
• W2358903369 hasConcept C22212356 @default.
• W2358903369 hasConcept C22507642 @default.
• W2358903369 hasConcept C2776214188 @default.
• W2358903369 hasConcept C2776371148 @default.
• W2358903369 hasConcept C2780179797 @default.
• W2358903369 hasConcept C2780378061 @default.
• W2358903369 hasConcept C33724603 @default.
• W2358903369 hasConcept C41008148 @default.
• W2358903369 hasConcept C42475967 @default.
• W2358903369 hasConcept C45235069 @default.
• W2358903369 hasConcept C49261128 @default.
• W2358903369 hasConcept C548081761 @default.
• W2358903369 hasConcept C78519656 @default.
• W2358903369 hasConceptScore W2358903369C107094494 @default.
• W2358903369 hasConceptScore W2358903369C107673813 @default.
• W2358903369 hasConceptScore W2358903369C112930515 @default.
• W2358903369 hasConceptScore W2358903369C124101348 @default.
• W2358903369 hasConceptScore W2358903369C127313418 @default.
• W2358903369 hasConceptScore W2358903369C127413603 @default.
• W2358903369 hasConceptScore W2358903369C144133560 @default.
• W2358903369 hasConceptScore W2358903369C154945302 @default.
• W2358903369 hasConceptScore W2358903369C160234255 @default.
• W2358903369 hasConceptScore W2358903369C162853370 @default.
• W2358903369 hasConceptScore W2358903369C165205528 @default.
• W2358903369 hasConceptScore W2358903369C175551986 @default.
• W2358903369 hasConceptScore W2358903369C178790620 @default.
• W2358903369 hasConceptScore W2358903369C178802073 @default.
• W2358903369 hasConceptScore W2358903369C185592680 @default.
• W2358903369 hasConceptScore W2358903369C18762648 @default.
• W2358903369 hasConceptScore W2358903369C200601418 @default.
• W2358903369 hasConceptScore W2358903369C22212356 @default.
• W2358903369 hasConceptScore W2358903369C22507642 @default.
• W2358903369 hasConceptScore W2358903369C2776214188 @default.
• W2358903369 hasConceptScore W2358903369C2776371148 @default.
• W2358903369 hasConceptScore W2358903369C2780179797 @default.
• W2358903369 hasConceptScore W2358903369C2780378061 @default.
• W2358903369 hasConceptScore W2358903369C33724603 @default.
• W2358903369 hasConceptScore W2358903369C41008148 @default.
• W2358903369 hasConceptScore W2358903369C42475967 @default.
• W2358903369 hasConceptScore W2358903369C45235069 @default.
• W2358903369 hasConceptScore W2358903369C49261128 @default.
• W2358903369 hasConceptScore W2358903369C548081761 @default.
• W2358903369 hasConceptScore W2358903369C78519656 @default.
• W2358903369 hasLocation W23589033691 @default.
• W2358903369 hasOpenAccess W2358903369 @default.
• W2358903369 hasPrimaryLocation W23589033691 @default.
• W2358903369 hasRelatedWork W1979136443 @default.
• W2358903369 hasRelatedWork W1980026941 @default.
• W2358903369 hasRelatedWork W1990801720 @default.
• W2358903369 hasRelatedWork W2010555599 @default.
• W2358903369 hasRelatedWork W2010792738 @default.
• W2358903369 hasRelatedWork W2280524283 @default.
• W2358903369 hasRelatedWork W2378131357 @default.
• W2358903369 hasRelatedWork W2386257519 @default.
• W2358903369 hasRelatedWork W2432823037 @default.
• W2358903369 hasRelatedWork W2473975479 @default.
• W2358903369 hasRelatedWork W2606387003 @default.
• W2358903369 hasRelatedWork W2800291282 @default.
• W2358903369 hasRelatedWork W2984192815 @default.
• W2358903369 hasRelatedWork W2988198258 @default.
• W2358903369 hasRelatedWork W3088032956 @default.
• W2358903369 hasRelatedWork W3205096326 @default.
• W2358903369 hasRelatedWork W596931862 @default.
• W2358903369 hasRelatedWork W613908354 @default.
• W2358903369 hasRelatedWork W631010494 @default.
• W2358903369 hasRelatedWork W658649004 @default.
• W2358903369 isParatext "false" @default.
• W2358903369 isRetracted "false" @default.
• W2358903369 magId "2358903369" @default.
• W2358903369 workType "article" @default.