IDEAS home Printed from https://ideas.repec.org/a/eee/reensy/v186y2019icp194-208.html
   My bibliography  Save this article

Combining association rules mining with complex networks to monitor coupled risks

Author

Listed:
  • Zhou, Ying
  • Li, Chenshuang
  • Ding, Lieyun
  • Sekula, Przemyslaw
  • Love, Peter E.D.
  • Zhou, Cheng

Abstract

Due to geotechnical uncertainties, existing underground infrastructure, the construction of deep-pit foundations in dense urban areas is particularly challenging as there is a propensity for building and structural settlement to occur. Recognizing the need to proactively manage safety risks during construction, a new risk analysis approach that combines complex networks and association rules mining (ARM) is proposed. An improved Apriori algorithm is developed to unearth abnormal monitoring types. Then, complex network theory is introduced to examine the characteristics of the coupled relationships existing between different types of abnormal monitoring types. This research identifies and examines complex network measures to understand the topology of settlement networks. It is revealed that settlement networks confirm to both scale-free and small-word properties indicating that risks are not random events. This new approach of combining ARM with complex network is applied to examine deep foundation pits that are constructed for a subway project in Wuhan, China. It is demonstrated that proposed approach can successfully reveal the association rules between safety risk monitoring types and the coupling of risks. Preventative actions can therefore be undertaken in advance to mitigate against potential risks that are identified from the abnormal monitoring combinations.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:reensy:v:186:y:2019:i:c:p:194-208
    DOI: 10.1016/j.ress.2019.02.013
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0951832018308135
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ress.2019.02.013?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. Khakzad, Nima & Khan, Faisal & Amyotte, Paul, 2011. "Safety analysis in process facilities: Comparison of fault tree and Bayesian network approaches," Reliability Engineering and System Safety, Elsevier, vol. 96(8), pages 925-932.
    2. Wu, Xianguo & Liu, Huitao & Zhang, Limao & Skibniewski, Miroslaw J. & Deng, Qianli & Teng, Jiaying, 2015. "A dynamic Bayesian network based approach to safety decision support in tunnel construction," Reliability Engineering and System Safety, Elsevier, vol. 134(C), pages 157-168.
    3. Long, Wen & Guan, Lijing & Shen, Jiangjian & Song, Linqiu & Cui, Lingxiao, 2017. "A complex network for studying the transmission mechanisms in stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 484(C), pages 345-357.
    4. Mahyar, Hamidreza & Hasheminezhad, Rouzbeh & Ghalebi K., Elahe & Nazemian, Ali & Grosu, Radu & Movaghar, Ali & Rabiee, Hamid R., 2018. "Compressive sensing of high betweenness centrality nodes in networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 497(C), pages 166-184.
    5. Fink, Olga & Zio, Enrico & Weidmann, Ulrich, 2014. "Predicting component reliability and level of degradation with complex-valued neural networks," Reliability Engineering and System Safety, Elsevier, vol. 121(C), pages 198-206.
    6. Feng, Jia & Li, Xiamiao & Mao, Baohua & Xu, Qi & Bai, Yun, 2017. "Weighted complex network analysis of the Beijing subway system: Train and passenger flows," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 474(C), pages 213-223.
    7. Cats, Oded & Koppenol, Gert-Jaap & Warnier, Martijn, 2017. "Robustness assessment of link capacity reduction for complex networks: Application for public transport systems," Reliability Engineering and System Safety, Elsevier, vol. 167(C), pages 544-553.
    8. Zhou, Ying & Li, Chenshuang & Zhou, Cheng & Luo, Hanbin, 2018. "Using Bayesian network for safety risk analysis of diaphragm wall deflection based on field data," Reliability Engineering and System Safety, Elsevier, vol. 180(C), pages 152-167.
    9. Khakzad, Nima & Khan, Faisal & Paltrinieri, Nicola, 2014. "On the application of near accident data to risk analysis of major accidents," Reliability Engineering and System Safety, Elsevier, vol. 126(C), pages 116-125.
    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. 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).
    2. 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).
    3. Yongshuai Sun & Zhiming Li, 2022. "Study on Design and Deformation Law of Pile-Anchor Support System in Deep Foundation Pit," Sustainability, MDPI, vol. 14(19), pages 1-18, September.
    4. Han-Hsiang Wang & Jieh-Haur Chen & Achmad Muhyidin Arifai & Masoud Gheisari, 2022. "Exploring Empirical Rules for Construction Accident Prevention Based on Unsafe Behaviors," Sustainability, MDPI, vol. 14(7), pages 1-9, March.
    5. 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).
    6. Wang, Qianlin & Han, Jiaqi & Chen, Feng & Hu, Su & Yun, Cheng & Dou, Zhan & Yan, Tingjun & Yang, Guoan, 2024. "Modeling risk characterization networks for chemical processes based on multi-variate data," Energy, Elsevier, vol. 293(C).
    7. Xiaoji Wan & Fen Chen & Hailin Li & Weibin Lin, 2022. "Potentially Related Commodity Discovery Based on Link Prediction," Mathematics, MDPI, vol. 10(19), pages 1-27, October.
    8. 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).
    9. 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).
    10. Yong Zhang & Qi Zhang & Xiang Zhang & Meng Li & Guoqing Qi, 2024. "How Do We Analyze the Accident Causation of Shield Construction of Water Conveyance Tunnels? A Method Based on the N-K Model and Complex Network," Mathematics, MDPI, vol. 12(20), pages 1-30, October.
    11. 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).
    12. Liu, Wenli & Li, Ang & Fang, Weili & Love, Peter E.D. & Hartmann, Timo & Luo, Hanbin, 2023. "A hybrid data-driven model for geotechnical reliability analysis," Reliability Engineering and System Safety, Elsevier, vol. 231(C).
    13. Ming Fang & Yi Zhang & Mengjue Zhu & Shaopei Chen, 2022. "Cause Mechanism of Metro Collapse Accident Based on Risk Coupling," IJERPH, MDPI, vol. 19(4), pages 1-18, February.
    14. Rossy Armyn Machfudiyanto & Jieh-Haur Chen & Yusuf Latief & Titi Sari Nurul Rachmawati & Achmad Muhyidin Arifai & Naufal Firmansyah, 2023. "Applying Association Rule Mining to Explore Unsafe Behaviors in the Indonesian Construction Industry," Sustainability, MDPI, vol. 15(6), pages 1-16, March.
    15. Wentao Wu & Shihai Wang & Bin Liu, 2024. "Software Fault Localization Based on Weighted Association Rule Mining and Complex Networks," Mathematics, MDPI, vol. 12(13), pages 1-22, July.
    16. Gaogeng Zhu & Guoming Chen & Jingyu Zhu & Xiangkun Meng & Xinhong Li, 2022. "Modeling the Evolution of Major Storm-Disaster-Induced Accidents in the Offshore Oil and Gas Industry," IJERPH, MDPI, vol. 19(12), pages 1-27, June.

    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. Guo, Qingjun & Amin, Shohel & Hao, Qianwen & Haas, Olivier, 2020. "Resilience assessment of safety system at subway construction sites applying analytic network process and extension cloud models," Reliability Engineering and System Safety, Elsevier, vol. 201(C).
    2. Zhang, Limao & Wu, Xianguo & Skibniewski, Miroslaw J. & Zhong, Jingbing & Lu, Yujie, 2014. "Bayesian-network-based safety risk analysis in construction projects," Reliability Engineering and System Safety, Elsevier, vol. 131(C), pages 29-39.
    3. Pan, Yue & Ou, Shenwei & Zhang, Limao & Zhang, Wenjing & Wu, Xianguo & Li, Heng, 2019. "Modeling risks in dependent systems: A Copula-Bayesian approach," Reliability Engineering and System Safety, Elsevier, vol. 188(C), pages 416-431.
    4. Zhang, Shuaishuai & Wu, Libo & Zhou, Yang, 2020. "The impact of negative list policy on sectoral structure: Based on complex network and DID analysis," Applied Energy, Elsevier, vol. 278(C).
    5. Wang, Fan & Li, Heng & Dong, Chao & Ding, Lieyun, 2019. "Knowledge representation using non-parametric Bayesian networks for tunneling risk analysis," Reliability Engineering and System Safety, Elsevier, vol. 191(C).
    6. Zhou, Jian-Lan & Lei, Yi, 2020. "A slim integrated with empirical study and network analysis for human error assessment in the railway driving process," Reliability Engineering and System Safety, Elsevier, vol. 204(C).
    7. Hongyang Yu & Faisal Khan & Brian Veitch, 2017. "A Flexible Hierarchical Bayesian Modeling Technique for Risk Analysis of Major Accidents," Risk Analysis, John Wiley & Sons, vol. 37(9), pages 1668-1682, September.
    8. Bhardwaj, U. & Teixeira, A.P. & Guedes Soares, C. & Ariffin, A.K. & Singh, S.S., 2021. "Evidence based risk analysis of fire and explosion accident scenarios in FPSOs," Reliability Engineering and System Safety, Elsevier, vol. 215(C).
    9. Rebello, Sinda & Yu, Hongyang & Ma, Lin, 2019. "An integrated approach for real-time hazard mitigation in complex industrial processes," Reliability Engineering and System Safety, Elsevier, vol. 188(C), pages 297-309.
    10. Yi Yang & John Dalsgaard Sørensen, 2020. "Probabilistic Availability Analysis for Marine Energy Transfer Subsystem Using Bayesian Network," Energies, MDPI, vol. 13(19), pages 1-27, October.
    11. Guo, Jian & Ma, Kaijiang, 2024. "Risk analysis for hazardous chemical vehicle-bridge transportation system: A dynamic Bayesian network model incorporating vehicle dynamics," Reliability Engineering and System Safety, Elsevier, vol. 242(C).
    12. Nima Khakzad & Sina Khakzad & Faisal Khan, 2014. "Probabilistic risk assessment of major accidents: application to offshore blowouts in the Gulf of Mexico," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 74(3), pages 1759-1771, December.
    13. Lin, Song-Shun & Shen, Shui-Long & Zhou, Annan & Xu, Ye-Shuang, 2021. "Novel model for risk identification during karst excavation," Reliability Engineering and System Safety, Elsevier, vol. 209(C).
    14. Mi, Jinhua & Li, Yan-Feng & Yang, Yuan-Jian & Peng, Weiwen & Huang, Hong-Zhong, 2016. "Reliability assessment of complex electromechanical systems under epistemic uncertainty," Reliability Engineering and System Safety, Elsevier, vol. 152(C), pages 1-15.
    15. Hong, Bingyuan & Shao, Bowen & Guo, Jian & Fu, Jianzhong & Li, Cuicui & Zhu, Baikang, 2023. "Dynamic Bayesian network risk probability evolution for third-party damage of natural gas pipelines," Applied Energy, Elsevier, vol. 333(C).
    16. Özgür-Ünlüakın, Demet & Türkali, Busenur & Karacaörenli, Ayşe & Çağlar Aksezer, S., 2019. "A DBN based reactive maintenance model for a complex system in thermal power plants," Reliability Engineering and System Safety, Elsevier, vol. 190(C), pages 1-1.
    17. KIM, Junyung & ZHAO, Xingang & SHAH, Asad Ullah Amin & KANG, Hyun Gook, 2021. "System risk quantification and decision making support using functional modeling and dynamic Bayesian network," Reliability Engineering and System Safety, Elsevier, vol. 215(C).
    18. Luo, Ding & Cats, Oded & van Lint, Hans & Currie, Graham, 2019. "Integrating network science and public transport accessibility analysis for comparative assessment," Journal of Transport Geography, Elsevier, vol. 80(C).
    19. Jinfen Zhang & Ângelo P Teixeira & C. Guedes Soares & Xinping Yan & Kezhong Liu, 2016. "Maritime Transportation Risk Assessment of Tianjin Port with Bayesian Belief Networks," Risk Analysis, John Wiley & Sons, vol. 36(6), pages 1171-1187, June.
    20. Zhang, Haoyuan & Marsh, D. William R, 2021. "Managing infrastructure asset: Bayesian networks for inspection and maintenance decisions reasoning and planning," Reliability Engineering and System Safety, Elsevier, vol. 207(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:186:y:2019:i:c:p:194-208. 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.