Fusing XGBoost and SHAP Models for Maritime Accident Prediction and Causality Interpretability Analysis

In order to prevent safety risks, control marine accidents and improve the overall safety of marine navigation, this study established a marine accident prediction model. The influences of management characteristics, environmental characteristics, personnel characteristics, ship characteristics, pil...

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Vydané v:Journal of marine science and engineering Ročník 10; číslo 8; s. 1154
Hlavní autori: Zhang, Cheng, Zou, Xiong, Lin, Chuan
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Basel MDPI AG 01.08.2022
Predmet:
Accident prevention
Algorithms
Casualties
causal analysis
Climate change
Coronaviruses
COVID-19
Crew
Environmental management
extreme gradient boosting algorithm
Human error
interpretable machine learning
Machine learning
Marine accidents
maritime accidents
Maritime safety
Navigation
Pilotage
Ports
Prediction models
Probability
Risk
Risk factors
risk prediction
Safety
Ship accidents & safety
Shipping
Surface navigation
Traffic accidents & safety
China
Zhejiang China
ISSN:2077-1312, 2077-1312
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Shrnutí:In order to prevent safety risks, control marine accidents and improve the overall safety of marine navigation, this study established a marine accident prediction model. The influences of management characteristics, environmental characteristics, personnel characteristics, ship characteristics, pilotage characteristics, wharf characteristics and other factors on the safety risk of maritime navigation are discussed. Based on the official data of Zhejiang Maritime Bureau, the extreme gradient boosting (XGBoost) algorithm was used to construct a maritime accident classification prediction model, and the explainable machine learning framework SHAP was used to analyze the causal factors of accident risk and the contribution of each feature to the occurrence of maritime accidents. The results show that the XGBoost algorithm can accurately predict the accident types of maritime accidents with an accuracy, precision and recall rate of 97.14%. The crew factor is an important factor affecting the safety risk of maritime navigation, whereas maintaining the equipment and facilities in good condition and improving the management level of shipping companies have positive effects on improving maritime safety. By explaining the correlation between maritime accident characteristics and maritime accidents, this study can provide scientific guidance for maritime management departments and ship companies regarding the control or management of maritime accident prevention.
Bibliografia:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:2077-1312
2077-1312
DOI:10.3390/jmse10081154