IDEAS home Printed from https://ideas.repec.org/a/eee/reensy/v230y2023ics095183202200549x.html
   My bibliography  Save this article

Determining the critical risk factors for predicting the severity of ship collision accidents using a data-driven approach

Author

Listed:
  • Lan, He
  • Ma, Xiaoxue
  • Qiao, Weiliang
  • Deng, Wanyi

Abstract

Ship collision accidents often result in serious casualties and property losses. Predicting the severity of ship collisions is beneficial to improve maritime transport safety. Therefore, this study proposes a data-driven approach integrating association rule mining (ARM), complex network (CN), and random forest (RF) to explore the correlation among risk factors and determine the critical risk factors for predicting the severity of ship collision accidents. Specifically, ARM is integrated with CN to develop the risk interaction network of ship collisions and to identify the criticality of risk factors. Then, RF is employed to predict the severity of ship collisions, and determine the risk factors that have a critical effect on severity prediction. The results show that poor team communication is the most critical risk factor for predicting the severity of ship collisions. Moreover, the criticality of risk factors is different in the risk networks and prediction model. Results from this study would help relevant stakeholders to assess current risks and tailor safety strategies to reduce the severity of ship collisions.

Suggested Citation

  • Lan, He & Ma, Xiaoxue & Qiao, Weiliang & Deng, Wanyi, 2023. "Determining the critical risk factors for predicting the severity of ship collision accidents using a data-driven approach," Reliability Engineering and System Safety, Elsevier, vol. 230(C).
    • Handle: RePEc:eee:reensy:v:230:y:2023:i:c:s095183202200549x
    DOI: 10.1016/j.ress.2022.108934
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S095183202200549X
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ress.2022.108934?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Zhang, Panpan & Wang, Tiandong & Yan, Jun, 2022. "PageRank centrality and algorithms for weighted, directed networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 586(C).
    2. Çakır, Erkan & Fışkın, Remzi & Sevgili, Coşkan, 2021. "Investigation of tugboat accidents severity: An application of association rule mining algorithms," Reliability Engineering and System Safety, Elsevier, vol. 209(C).
    3. Galateia Terti & Isabelle Ruin & Jonathan J. Gourley & Pierre Kirstetter & Zachary Flamig & Juliette Blanchet & Ami Arthur & Sandrine Anquetin, 2019. "Toward Probabilistic Prediction of Flash Flood Human Impacts," Risk Analysis, John Wiley & Sons, vol. 39(1), pages 140-161, January.
    4. Lam, C.Y. & Tai, K., 2020. "Network topological approach to modeling accident causations and characteristics: Analysis of railway incidents in Japan," Reliability Engineering and System Safety, Elsevier, vol. 193(C).
    5. Zhaochen Wang & Jingbo Yin, 2020. "Risk assessment of inland waterborne transportation using data mining," Maritime Policy & Management, Taylor & Francis Journals, vol. 47(5), pages 633-648, July.
    6. Ma, Xiaoxue & Deng, Wanyi & Qiao, Weiliang & Lan, He, 2022. "A methodology to quantify the risk propagation of hazardous events for ship grounding accidents based on directed CN," Reliability Engineering and System Safety, Elsevier, vol. 221(C).
    7. Sotiralis, P. & Ventikos, N.P. & Hamann, R. & Golyshev, P. & Teixeira, A.P., 2016. "Incorporation of human factors into ship collision risk models focusing on human centred design aspects," Reliability Engineering and System Safety, Elsevier, vol. 156(C), pages 210-227.
    8. Huang, Wencheng & Kou, Xingyi & Zhang, Yue & Mi, Rongwei & Yin, Dezhi & Xiao, Wei & Liu, Zhanru, 2021. "Operational failure analysis of high-speed electric multiple units: A Bayesian network-K2 algorithm-expectation maximization approach," Reliability Engineering and System Safety, Elsevier, vol. 205(C).
    9. Zhou, Xiaoyi & Lu, Pan & Zheng, Zijian & Tolliver, Denver & Keramati, Amin, 2020. "Accident Prediction Accuracy Assessment for Highway-Rail Grade Crossings Using Random Forest Algorithm Compared with Decision Tree," Reliability Engineering and System Safety, Elsevier, vol. 200(C).
    10. Mi, Jinhua & Lu, Ning & Li, Yan-Feng & Huang, Hong-Zhong & Bai, Libing, 2022. "An evidential network-based hierarchical method for system reliability analysis with common cause failures and mixed uncertainties," Reliability Engineering and System Safety, Elsevier, vol. 220(C).
    11. Lan, He & Ma, Xiaoxue & Ma, Laihao & Qiao, Weiliang, 2023. "Pattern investigation of total loss maritime accidents based on association rule mining," Reliability Engineering and System Safety, Elsevier, vol. 229(C).
    12. Lan, He & Ma, Xiaoxue & Qiao, Weiliang & Ma, Laihao, 2022. "On the causation of seafarers’ unsafe acts using grounded theory and association rule," Reliability Engineering and System Safety, Elsevier, vol. 223(C).
    13. Qiao, Wanguan & Liu, Quanlong & Li, Xinchun & Luo, Xixi & Wan, YuLong, 2018. "Using data mining techniques to analyze the influencing factor of unsafe behaviors in Chinese underground coal mines," Resources Policy, Elsevier, vol. 59(C), pages 210-216.
    14. Wang, Huanxin & Liu, Zhengjiang & Wang, Xinjian & Graham, Tony & Wang, Jin, 2021. "An analysis of factors affecting the severity of marine accidents," Reliability Engineering and System Safety, Elsevier, vol. 210(C).
    15. Jia, Xiaohui & Zhang, Donghui, 2021. "Prediction of maritime logistics service risks applying soft set based association rule: An early warning model," Reliability Engineering and System Safety, Elsevier, vol. 207(C).
    16. Fu, Lipeng & Wang, Xueqing & Zhao, Heng & Li, Mengnan, 2022. "Interactions among safety risks in metro deep foundation pit projects: An association rule mining-based modeling framework," Reliability Engineering and System Safety, Elsevier, vol. 221(C).
    17. Zhou, Ying & Li, Chenshuang & Ding, Lieyun & Sekula, Przemyslaw & Love, Peter E.D. & Zhou, Cheng, 2019. "Combining association rules mining with complex networks to monitor coupled risks," Reliability Engineering and System Safety, Elsevier, vol. 186(C), pages 194-208.
    18. Bye, Rolf J. & Aalberg, Asbjørn L., 2018. "Maritime navigation accidents and risk indicators: An exploratory statistical analysis using AIS data and accident reports," Reliability Engineering and System Safety, Elsevier, vol. 176(C), pages 174-186.
    19. Weiliang Qiao & Yu Liu & Xiaoxue Ma & Yang Liu, 2020. "Human Factors Analysis for Maritime Accidents Based on a Dynamic Fuzzy Bayesian Network," Risk Analysis, John Wiley & Sons, vol. 40(5), pages 957-980, May.
    20. Kaptan, Mehmet & Uğurlu, Özkan & Wang, Jin, 2021. "The effect of nonconformities encountered in the use of technology on the occurrence of collision, contact and grounding accidents," Reliability Engineering and System Safety, Elsevier, vol. 215(C).
    21. Liu, Zengkai & Ma, Qiang & Cai, Baoping & Shi, Xuewei & Zheng, Chao & Liu, Yonghong, 2022. "Risk coupling analysis of subsea blowout accidents based on dynamic Bayesian network and NK model," Reliability Engineering and System Safety, Elsevier, vol. 218(PA).
    22. Matthew R. Hallowell & Dillon Alexander & John A. Gambatese, 2017. "Energy-based safety risk assessment: does magnitude and intensity of energy predict injury severity?," Construction Management and Economics, Taylor & Francis Journals, vol. 35(1-2), pages 64-77, February.
    23. Guo, Shengyu & Zhou, Xinyu & Tang, Bing & Gong, Peisong, 2020. "Exploring the behavioral risk chains of accidents using complex network theory in the construction industry," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 560(C).
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Alfarizi, Muhammad Gibran & Ustolin, Federico & Vatn, Jørn & Yin, Shen & Paltrinieri, Nicola, 2023. "Towards accident prevention on liquid hydrogen: A data-driven approach for releases prediction," Reliability Engineering and System Safety, Elsevier, vol. 236(C).
    2. Rong, H. & Teixeira, A.P. & Guedes Soares, C., 2024. "A framework for ship abnormal behaviour detection and classification using AIS data," Reliability Engineering and System Safety, Elsevier, vol. 247(C).
    3. Li, Xin & Chen, Chao & Hong, Yi-du & Yang, Fu-qiang, 2023. "Exploring hazardous chemical explosion accidents with association rules and Bayesian networks," Reliability Engineering and System Safety, Elsevier, vol. 233(C).
    4. Sun, Xuting & Hu, Yue & Qin, Yichen & Zhang, Yuan, 2024. "Risk assessment of unmanned aerial vehicle accidents based on data-driven Bayesian networks," Reliability Engineering and System Safety, Elsevier, vol. 248(C).
    5. Wu, Pengcheng & Chen, Jun, 2024. "Data-driven zonotopic approximation for n-dimensional probabilistic geofencing," Reliability Engineering and System Safety, Elsevier, vol. 244(C).
    6. Wang, Hong & Chen, Ning & Wu, Bing & Guedes Soares, C., 2024. "Human and organizational factors analysis of collision accidents between merchant ships and fishing vessels based on HFACS-BN model," Reliability Engineering and System Safety, Elsevier, vol. 249(C).
    7. Liu, Jintao & Chen, Keyi & Duan, Huayu & Li, Chenling, 2024. "A knowledge graph-based hazard prediction approach for preventing railway operational accidents," Reliability Engineering and System Safety, Elsevier, vol. 247(C).
    8. Zhou, Kaiwen & Xing, Wenbin & Wang, Jingbo & Li, Huanhuan & Yang, Zaili, 2024. "A data-driven risk model for maritime casualty analysis: A global perspective," Reliability Engineering and System Safety, Elsevier, vol. 244(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Lan, He & Ma, Xiaoxue & Qiao, Weiliang & Ma, Laihao, 2022. "On the causation of seafarers’ unsafe acts using grounded theory and association rule," Reliability Engineering and System Safety, Elsevier, vol. 223(C).
    2. Lan, He & Ma, Xiaoxue & Ma, Laihao & Qiao, Weiliang, 2023. "Pattern investigation of total loss maritime accidents based on association rule mining," Reliability Engineering and System Safety, Elsevier, vol. 229(C).
    3. Zhang, Hengqi & Geng, Hua, 2023. "A methodology to identify and assess high-risk causes for electrical personal accidents based on directed weighted CN," Reliability Engineering and System Safety, Elsevier, vol. 231(C).
    4. Ma, Xiaoxue & Deng, Wanyi & Qiao, Weiliang & Lan, He, 2022. "A methodology to quantify the risk propagation of hazardous events for ship grounding accidents based on directed CN," Reliability Engineering and System Safety, Elsevier, vol. 221(C).
    5. Wang, Wenhao & Wang, Yanhui & Wang, Guangxing & Li, Man & Jia, Limin, 2023. "Identification of the critical accident causative factors in the urban rail transit system by complex network theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 610(C).
    6. Li, Xin & Chen, Chao & Hong, Yi-du & Yang, Fu-qiang, 2023. "Exploring hazardous chemical explosion accidents with association rules and Bayesian networks," Reliability Engineering and System Safety, Elsevier, vol. 233(C).
    7. Fu, Shanshan & Yu, Yuerong & Chen, Jihong & Xi, Yongtao & Zhang, Mingyang, 2022. "A framework for quantitative analysis of the causation of grounding accidents in arctic shipping," Reliability Engineering and System Safety, Elsevier, vol. 226(C).
    8. Wang, Hong & Chen, Ning & Wu, Bing & Guedes Soares, C., 2024. "Human and organizational factors analysis of collision accidents between merchant ships and fishing vessels based on HFACS-BN model," Reliability Engineering and System Safety, Elsevier, vol. 249(C).
    9. Liu, Zhichen & Li, Ying & Zhang, Zhaoyi & Yu, Wenbo, 2022. "A new evacuation accessibility analysis approach based on spatial information," Reliability Engineering and System Safety, Elsevier, vol. 222(C).
    10. Sezer, Sukru Ilke & Camliyurt, Gokhan & Aydin, Muhmmet & Akyuz, Emre & Gardoni, Paolo, 2023. "A bow-tie extended D-S evidence-HEART modelling for risk analysis of cargo tank cracks on oil/chemical tanker," Reliability Engineering and System Safety, Elsevier, vol. 237(C).
    11. Yu, Qing & Liu, Kezhong & Chang, Chia-Hsun & Yang, Zaili, 2020. "Realising advanced risk assessment of vessel traffic flows near offshore wind farms," Reliability Engineering and System Safety, Elsevier, vol. 203(C).
    12. Liu, Yang & Ma, Xiaoxue & Qiao, Weiliang & Ma, Laihao & Han, Bing, 2024. "A novel methodology to model disruption propagation for resilient maritime transportation systems–a case study of the Arctic maritime transportation system," Reliability Engineering and System Safety, Elsevier, vol. 241(C).
    13. Jiao Liu & Shuang Li & Weijun Bao & Kun Xu, 2022. "Could the Management System of Safety Partnership Change Miners’ Unsafe Behavior?," Sustainability, MDPI, vol. 14(20), pages 1-14, October.
    14. Zhang, Hengqi & Geng, Hua & Zeng, Huarong & Jiang, Li, 2023. "Dynamic risk evaluation and control of electrical personal accidents," Reliability Engineering and System Safety, Elsevier, vol. 237(C).
    15. Chen, Xiyuan & Ma, Xiaoping & Jia, Limin & Zhang, Zhipeng & Chen, Fei & Wang, Ruojin, 2024. "Causative analysis of freight railway accident in specific scenes using a data-driven Bayesian network," Reliability Engineering and System Safety, Elsevier, vol. 243(C).
    16. Hai, Nan & Gong, Daqing & Liu, Shifeng & Dai, Zixuan, 2022. "Dynamic coupling risk assessment model of utility tunnels based on multimethod fusion," Reliability Engineering and System Safety, Elsevier, vol. 228(C).
    17. Ung, S.T., 2021. "Navigation Risk estimation using a modified Bayesian Network modeling-a case study in Taiwan," Reliability Engineering and System Safety, Elsevier, vol. 213(C).
    18. Yu, Qing & Teixeira, Ângelo Palos & Liu, Kezhong & Rong, Hao & Guedes Soares, Carlos, 2021. "An integrated dynamic ship risk model based on Bayesian Networks and Evidential Reasoning," Reliability Engineering and System Safety, Elsevier, vol. 216(C).
    19. Cai, Mingyou & Zhang, Jinfen & Zhang, Di & Yuan, Xiaoli & Soares, C. Guedes, 2021. "Collision risk analysis on ferry ships in Jiangsu Section of the Yangtze River based on AIS data," Reliability Engineering and System Safety, Elsevier, vol. 215(C).
    20. Li, Huanhuan & Ren, Xujie & Yang, Zaili, 2023. "Data-driven Bayesian network for risk analysis of global maritime accidents," Reliability Engineering and System Safety, Elsevier, vol. 230(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:reensy:v:230:y:2023:i:c:s095183202200549x. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/reliability-engineering-and-system-safety .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.