Risk Reasoning from Factor Correlation of Maritime Traffic under Arctic Sea Ice Status Association with a Bayesian Belief Network

Sustainable growth should not only be beneficial to the shipping industry in the future, but is also an urgent need to respond to resource and environmental crises and strengthen shipping governance. Maritime traffic in Arctic waters is prone to encounter dangerous ice conditions, and it is essentia...

Full description

Bibliographic Details
Published in:Sustainability
Main Authors: Zhuang Li, Shenping Hu, Guoping Gao, Yongtao Xi, Shanshan Fu, Chenyang Yao
Format: Article in Journal/Newspaper
Language:English
Published: MDPI AG 2020
Subjects:
geo
Online Access:https://doi.org/10.3390/su13010147
https://doaj.org/article/3f5e6997a7a84a0db30dfeb440661c86
id fttriple:oai:gotriple.eu:oai:doaj.org/article:3f5e6997a7a84a0db30dfeb440661c86
record_format openpolar
spelling fttriple:oai:gotriple.eu:oai:doaj.org/article:3f5e6997a7a84a0db30dfeb440661c86 2023-05-15T14:37:40+02:00 Risk Reasoning from Factor Correlation of Maritime Traffic under Arctic Sea Ice Status Association with a Bayesian Belief Network Zhuang Li Shenping Hu Guoping Gao Yongtao Xi Shanshan Fu Chenyang Yao 2020-12-01 https://doi.org/10.3390/su13010147 https://doaj.org/article/3f5e6997a7a84a0db30dfeb440661c86 en eng MDPI AG doi:10.3390/su13010147 2071-1050 https://doaj.org/article/3f5e6997a7a84a0db30dfeb440661c86 undefined Sustainability, Vol 13, Iss 147, p 147 (2020) maritime traffic risk ship-ice collision Bayesian network Dempster-Shafer theory Arctic waters dynamic association geo envir Journal Article https://vocabularies.coar-repositories.org/resource_types/c_6501/ 2020 fttriple https://doi.org/10.3390/su13010147 2023-01-22T19:00:15Z Sustainable growth should not only be beneficial to the shipping industry in the future, but is also an urgent need to respond to resource and environmental crises and strengthen shipping governance. Maritime traffic in Arctic waters is prone to encounter dangerous ice conditions, and it is essential to study the mechanism of ice collision risk formation in relation to ice conditions. Taking the ship-ice collision risk in Arctic waters as the research object, we propose a dynamic assessment model of ship-ice collision risk under sea ice status dynamic association (SDA) effect. By constructing the standard paradigm of risk factor dynamic association (DA) effect, taking SDA as the key association factor. Combing with other risk factors that affect ship-ice collision accidents, the coupling relationship between risk factors were analyzed. Then, using the Bayesian network method to build a ship-ice collision accident dynamic risk assessment model and combing with the ice monitoring data in summer Arctic waters, we screen five ships’ position information on the trans-Arctic route in August. The risk behavior of ship-ice collision accidents on the selected route under SDA is analyzed by model simulation. The research reveal that the degree of SDA is a key related factor for the serious ice condition and the possibility of human error during ship’s navigation, which significantly affects the ship-ice collision risk. The traffic in Arctic waters requires extra vigilance of the SDA effect from no ice threat to ice threat, and continuous ice threat. According to the ship-ice collision risk analysis under the SDA effect and without SDA effect, the difference in risk reasoning results on the five stations of the selected route are 32.69%, −32.33%, −27.64%, −10.26%, and −30.13% respectively. The DA effect can optimize ship-ice collision risk inference problem in Arctic waters. Article in Journal/Newspaper Arctic Sea ice Unknown Arctic Sustainability 13 1 147
institution Open Polar
collection Unknown
op_collection_id fttriple
language English
topic maritime traffic risk
ship-ice collision
Bayesian network
Dempster-Shafer theory
Arctic waters
dynamic association
geo
envir
spellingShingle maritime traffic risk
ship-ice collision
Bayesian network
Dempster-Shafer theory
Arctic waters
dynamic association
geo
envir
Zhuang Li
Shenping Hu
Guoping Gao
Yongtao Xi
Shanshan Fu
Chenyang Yao
Risk Reasoning from Factor Correlation of Maritime Traffic under Arctic Sea Ice Status Association with a Bayesian Belief Network
topic_facet maritime traffic risk
ship-ice collision
Bayesian network
Dempster-Shafer theory
Arctic waters
dynamic association
geo
envir
description Sustainable growth should not only be beneficial to the shipping industry in the future, but is also an urgent need to respond to resource and environmental crises and strengthen shipping governance. Maritime traffic in Arctic waters is prone to encounter dangerous ice conditions, and it is essential to study the mechanism of ice collision risk formation in relation to ice conditions. Taking the ship-ice collision risk in Arctic waters as the research object, we propose a dynamic assessment model of ship-ice collision risk under sea ice status dynamic association (SDA) effect. By constructing the standard paradigm of risk factor dynamic association (DA) effect, taking SDA as the key association factor. Combing with other risk factors that affect ship-ice collision accidents, the coupling relationship between risk factors were analyzed. Then, using the Bayesian network method to build a ship-ice collision accident dynamic risk assessment model and combing with the ice monitoring data in summer Arctic waters, we screen five ships’ position information on the trans-Arctic route in August. The risk behavior of ship-ice collision accidents on the selected route under SDA is analyzed by model simulation. The research reveal that the degree of SDA is a key related factor for the serious ice condition and the possibility of human error during ship’s navigation, which significantly affects the ship-ice collision risk. The traffic in Arctic waters requires extra vigilance of the SDA effect from no ice threat to ice threat, and continuous ice threat. According to the ship-ice collision risk analysis under the SDA effect and without SDA effect, the difference in risk reasoning results on the five stations of the selected route are 32.69%, −32.33%, −27.64%, −10.26%, and −30.13% respectively. The DA effect can optimize ship-ice collision risk inference problem in Arctic waters.
format Article in Journal/Newspaper
author Zhuang Li
Shenping Hu
Guoping Gao
Yongtao Xi
Shanshan Fu
Chenyang Yao
author_facet Zhuang Li
Shenping Hu
Guoping Gao
Yongtao Xi
Shanshan Fu
Chenyang Yao
author_sort Zhuang Li
title Risk Reasoning from Factor Correlation of Maritime Traffic under Arctic Sea Ice Status Association with a Bayesian Belief Network
title_short Risk Reasoning from Factor Correlation of Maritime Traffic under Arctic Sea Ice Status Association with a Bayesian Belief Network
title_full Risk Reasoning from Factor Correlation of Maritime Traffic under Arctic Sea Ice Status Association with a Bayesian Belief Network
title_fullStr Risk Reasoning from Factor Correlation of Maritime Traffic under Arctic Sea Ice Status Association with a Bayesian Belief Network
title_full_unstemmed Risk Reasoning from Factor Correlation of Maritime Traffic under Arctic Sea Ice Status Association with a Bayesian Belief Network
title_sort risk reasoning from factor correlation of maritime traffic under arctic sea ice status association with a bayesian belief network
publisher MDPI AG
publishDate 2020
url https://doi.org/10.3390/su13010147
https://doaj.org/article/3f5e6997a7a84a0db30dfeb440661c86
geographic Arctic
geographic_facet Arctic
genre Arctic
Sea ice
genre_facet Arctic
Sea ice
op_source Sustainability, Vol 13, Iss 147, p 147 (2020)
op_relation doi:10.3390/su13010147
2071-1050
https://doaj.org/article/3f5e6997a7a84a0db30dfeb440661c86
op_rights undefined
op_doi https://doi.org/10.3390/su13010147
container_title Sustainability
container_volume 13
container_issue 1
container_start_page 147
_version_ 1766309879999365120