A qualitative approach to risk management of hazardous materials in the Netherlands: lessons learned from 7 sluice cases

Vlies, Vincent van der

doi:10.1080/13669877.2014.940595

Cited by 3 publications

(1 citation statement)

References 7 publications

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“…Vlies et al put forward a qualitative risk assessment method for dangerous goods through seven case studies in the Netherlands. This method can effectively control the external safety risks related to waterway transportation [19]. The research above constructs decision-making to reduce risks by analyzing the risks in the process of dangerous goods transportation.…”

Section: Literature Reviewmentioning

confidence: 99%

Construction of Knowledge Graphs for Maritime Dangerous Goods

et al. 2019

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Dangerous goods occupy an important proportion in international shipping, and government and enterprises pay a lot of attention to transport safety. There are a wide variety of dangerous goods, and the knowledge involved is extensive and complex. Organizing and managing this knowledge plays an important role in the safe transportation of dangerous goods. The knowledge graph is a mass of brand-new knowledge management technologies that provide powerful technical support for integrating domain knowledge and solving the problem of the “knowledge island.” This paper first introduces the knowledge of maritime dangerous goods (MDG); constructs a three-layer knowledge structure of MDG, dividing this knowledge into two categories; uses ontology to express the concepts, entities, and relations of MDG; and puts forward the representation methods of the conceptual layer and entity layer and designs them in detail. Finally, the knowledge graph of maritime dangerous goods (KGMDG) is constructed. Furthermore, we demonstrate the knowledge visualization, retrieval, and automatic judgment of segregation requirement based on KGMDG. It is proved that KGMDG does not only help to simplify the retrieval process of professional knowledge and to promote intelligent transportation but is also conducive to the sharing, dissemination, and utilization of MDG knowledge.

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Section: Literature Reviewmentioning

confidence: 99%