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...
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2020
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Online Access: | https://doi.org/10.3390/su13010147 https://doaj.org/article/3f5e6997a7a84a0db30dfeb440661c86 |
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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 |
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1766309879999365120 |