Research on Quantitative Risk Assessment Method of Packaged Cargoes Carried by Ship Based on Online Dynamic Big Data Fusion Technology

0Citations
Citations of this article
12Readers
Mendeley users who have this article in their library.

This article is free to access.

Abstract

In this paper, a quantitative risk assessment method of packaged cargoes carried by ship based on online dynamic big data fusion technology was researched. In recent years, major accidents such as oil spill, fire, explosion and ship loss occurred frequently in shipborne cargo transportation. Due to the lack of real-time dynamic risk analysis, both early warning and emergency handling of those accidents are extremely difficult. In this paper, a risk transmission model was built, which based on the flow chain for cargo transportation. A system including the analysis of cargo transportation risk and quantitative assessment model based on real-time dynamic big data fusion technology was built. Finally, a scientific quantitative assessment method was formed. And a container ship passing through Shenzhen waters was taken as an example in order to verify the practicality of the method. In this way, it can realize the quantitative assessment of risk (especially the risk of dangerous packaged cargoes)in the waterage. What's more, according to the assessment results, it can analyze the high-risk factors and high-risk parts in the process of waterage, and then realize the informationalized and modernized intelligent supervision in a whole process and all round way, which will effectively improve the level of accident prevention in China.

Cite

CITATION STYLE

APA

Lan, R., Chang, W., Shen, W., & Jia, Z. (2019). Research on Quantitative Risk Assessment Method of Packaged Cargoes Carried by Ship Based on Online Dynamic Big Data Fusion Technology. In Journal of Physics: Conference Series (Vol. 1187). Institute of Physics Publishing. https://doi.org/10.1088/1742-6596/1187/5/052087

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free