IDEAS home Printed from https://ideas.repec.org/a/eee/reensy/v228y2022ics0951832022003738.html
   My bibliography  Save this article

A model fusion strategy for identifying aircraft risk using CNN and Att-BiLSTM

Author

Listed:
  • Zhou, Di
  • Zhuang, Xiao
  • Zuo, Hongfu
  • Cai, Jing
  • Zhao, Xufeng
  • Xiang, Jiawei

Abstract

The Aviation Safety Reporting System (ASRS) data is an important information source for risk identification in civil aviation. However, ASRS data has the characteristics of high dimensionality, unstructured and data imbalance. This brings great challenges for risk identification. In this paper, a model fusion strategy is proposed for identifying the aircraft risk by using convolutional neural network (CNN) and bidirectional long short-term memory neural network with attention mechanism (Att-BiLSTM). Firstly, all obtained ASRS data are reasonably divided into five risk levels. Secondly, the CNN is utilized to deeply mine the relationship between risk levels and structured data. Meanwhile, the Att-BiLSTM is adopted to deeply mine the relationship between risk levels and unstructured event narratives. Finally, a model fusion strategy is proposed to fuse the preliminary identifications of CNN and Att-BiLSTM to obtain the final identifications. The adopted CNN and Att-BiLSTM are compared with two individual models respectively. The experimental results show that the CNN and Att-BiLSTM have superior identification performance. Furthermore, by comparing the performance of the proposed model fusion strategy against the effect of using the individual model, the proposed model fusion strategy is effective in improving identification accuracy and reducing the influence of data imbalance in civil aviation.

Suggested Citation

  • Zhou, Di & Zhuang, Xiao & Zuo, Hongfu & Cai, Jing & Zhao, Xufeng & Xiang, Jiawei, 2022. "A model fusion strategy for identifying aircraft risk using CNN and Att-BiLSTM," Reliability Engineering and System Safety, Elsevier, vol. 228(C).
    • Handle: RePEc:eee:reensy:v:228:y:2022:i:c:s0951832022003738
    DOI: 10.1016/j.ress.2022.108750
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0951832022003738
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ress.2022.108750?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. Saleh, J.H. & Marais, K.B. & Bakolas, E. & Cowlagi, R.V., 2010. "Highlights from the literature on accident causation and system safety: Review of major ideas, recent contributions, and challenges," Reliability Engineering and System Safety, Elsevier, vol. 95(11), pages 1105-1116.
    2. Lee, Juseong & Mitici, Mihaela, 2020. "An integrated assessment of safety and efficiency of aircraft maintenance strategies using agent-based modelling and stochastic Petri nets," Reliability Engineering and System Safety, Elsevier, vol. 202(C).
    3. Zhang, Xiaoge & Mahadevan, Sankaran, 2021. "Bayesian network modeling of accident investigation reports for aviation safety assessment," Reliability Engineering and System Safety, Elsevier, vol. 209(C).
    4. Wang, Yuhao & Pang, Yutian & Chen, Oliver & Iyer, Hari N. & Dutta, Parikshit & Menon, P.K. & Liu, Yongming, 2021. "Uncertainty quantification and reduction in aircraft trajectory prediction using Bayesian-Entropy information fusion," Reliability Engineering and System Safety, Elsevier, vol. 212(C).
    5. Liu, Yu & Wang, Weijie & Huang, Hong-Zhong & Li, Yanfeng & Yang, Yuanjian, 2014. "A new simulation model for assessing aircraft emergency evacuation considering passenger physical characteristics," Reliability Engineering and System Safety, Elsevier, vol. 121(C), pages 187-197.
    6. Liu, Lu & Song, Xiao & Zhou, Zhetao, 2022. "Aircraft engine remaining useful life estimation via a double attention-based data-driven architecture," Reliability Engineering and System Safety, Elsevier, vol. 221(C).
    7. Rose, Rodrigo L. & Puranik, Tejas G. & Mavris, Dimitri N. & Rao, Arjun H., 2022. "Application of structural topic modeling to aviation safety data," Reliability Engineering and System Safety, Elsevier, vol. 224(C).
    8. Xu, Bin & Wu, Qi & Xi, Chen & He, Ren, 2020. "Recognition of the fatigue status of pilots using BF–PSO optimized multi-class GP classification with sEMG signals," Reliability Engineering and System Safety, Elsevier, vol. 199(C).
    9. Barker, Kash & Ramirez-Marquez, Jose Emmanuel & Rocco, Claudio M., 2013. "Resilience-based network component importance measures," Reliability Engineering and System Safety, Elsevier, vol. 117(C), pages 89-97.
    10. Stroeve, Sybert H. & Som, Pradip & van Doorn, Bas A. & (Bert) Bakker, G.J., 2016. "Strengthening air traffic safety management by moving from outcome-based towards risk-based evaluation of runway incursions," Reliability Engineering and System Safety, Elsevier, vol. 147(C), pages 93-108.
    11. Zhou, Hang & Lopes Genez, Thiago Augusto & Brintrup, Alexandra & Parlikad, Ajith Kumar, 2022. "A hybrid-learning decomposition algorithm for competing risk identification within fleets of complex engineering systems," Reliability Engineering and System Safety, Elsevier, vol. 217(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. Wang, Jian & Liu, Huiyuan & Gao, Shibin & Yu, Long & Liu, Xingyang & Zhang, Dongkai & Kou, Lei, 2024. "Robust deep Gaussian process-based trustworthy fog-haze-caused pollution flashover prediction approach for overhead contact lines," Reliability Engineering and System Safety, Elsevier, vol. 243(C).
    2. Dong, Juan & Xing, Liwen & Cui, Ningbo & Zhao, Lu & Guo, Li & Wang, Zhihui & Du, Taisheng & Tan, Mingdong & Gong, Daozhi, 2024. "Estimating reference crop evapotranspiration using improved convolutional bidirectional long short-term memory network by multi-head attention mechanism in the four climatic zones of China," Agricultural Water Management, Elsevier, vol. 292(C).
    3. Hu, Deng & Wang, Hechun & Yang, Chuanlei & Wang, Binbin & Duan, Baoyin & Wang, Yinyan & Li, Hucai, 2024. "Construction of digital twin model of engine in-cylinder combustion based on data-driven," Energy, Elsevier, vol. 293(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. Rose, Rodrigo L. & Puranik, Tejas G. & Mavris, Dimitri N. & Rao, Arjun H., 2022. "Application of structural topic modeling to aviation safety data," Reliability Engineering and System Safety, Elsevier, vol. 224(C).
    2. Miriam Andrejiova & Anna Grincova & Daniela Marasova & Peter Koščák, 2021. "Civil Aviation Occurrences in Slovakia and Their Evaluation Using Statistical Methods," Sustainability, MDPI, vol. 13(10), pages 1-17, May.
    3. Dai, Wei & Quek, Zhi Hao & Low, Kin Huat, 2024. "Probabilistic modeling and reasoning of conflict detection effectiveness by tracking systems towards safe urban air mobility operations," Reliability Engineering and System Safety, Elsevier, vol. 244(C).
    4. Wen, Tao & Gao, Qiuya & Chen, Yu-wang & Cheong, Kang Hao, 2022. "Exploring the vulnerability of transportation networks by entropy: A case study of Asia–Europe maritime transportation network," Reliability Engineering and System Safety, Elsevier, vol. 226(C).
    5. Trucco, Paolo & Petrenj, Boris, 2023. "Characterisation of resilience metrics in full-scale applications to interdependent infrastructure systems," Reliability Engineering and System Safety, Elsevier, vol. 235(C).
    6. Jiang, Deyin & Chen, Tianyu & Xie, Juanzhang & Cui, Weimin & Song, Bifeng, 2023. "A mechanical system reliability degradation analysis and remaining life estimation method——With the example of an aircraft hatch lock mechanism," Reliability Engineering and System Safety, Elsevier, vol. 230(C).
    7. Churchwell, Jared S. & Zhang, Katherine S. & Saleh, Joseph H., 2018. "Epidemiology of helicopter accidents: Trends, rates, and covariates," Reliability Engineering and System Safety, Elsevier, vol. 180(C), pages 373-384.
    8. Ewa DUDEK & Karolina KRZYKOWSKA-PIOTROWSKA & Mirosław SIERGIEJCZYK, 2020. "Risk Management In (Air) Transport With Exemplary Risk Analysis Based On The Tolerability Matrix," Transport Problems, Silesian University of Technology, Faculty of Transport, vol. 15(2), pages 143-156, June.
    9. Hao, Yucheng & Jia, Limin & Zio, Enrico & Wang, Yanhui & Small, Michael & Li, Man, 2023. "Improving resilience of high-speed train by optimizing repair strategies," Reliability Engineering and System Safety, Elsevier, vol. 237(C).
    10. Ziegler Haselein, Bruno & da Silva, Jonny Carlos & Hooey, Becky L., 2024. "Multiple machine learning modeling on near mid-air collisions: An approach towards probabilistic reasoning," Reliability Engineering and System Safety, Elsevier, vol. 244(C).
    11. Janssens, Jochen & Talarico, Luca & Sörensen, Kenneth, 2016. "A hybridised variable neighbourhood tabu search heuristic to increase security in a utility network," Reliability Engineering and System Safety, Elsevier, vol. 145(C), pages 221-230.
    12. Zou, Qiling & Chen, Suren, 2019. "Enhancing resilience of interdependent traffic-electric power system," Reliability Engineering and System Safety, Elsevier, vol. 191(C).
    13. Hongyan Dui & Xinyue Wang & Haohao Zhou, 2023. "Redundancy-Based Resilience Optimization of Multi-Component Systems," Mathematics, MDPI, vol. 11(14), pages 1-16, July.
    14. Baroud, Hiba & Barker, Kash & Ramirez-Marquez, Jose E. & Rocco S., Claudio M., 2014. "Importance measures for inland waterway network resilience," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 62(C), pages 55-67.
    15. Kamei, Sayaka & Taghipour, Sharareh, 2023. "A comparison study of centralized and decentralized federated learning approaches utilizing the transformer architecture for estimating remaining useful life," Reliability Engineering and System Safety, Elsevier, vol. 233(C).
    16. Ayoub, Ali & Stankovski, Andrej & Kröger, Wolfgang & Sornette, Didier, 2021. "Precursors and startling lessons: Statistical analysis of 1250 events with safety significance from the civil nuclear sector," Reliability Engineering and System Safety, Elsevier, vol. 214(C).
    17. 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).
    18. Konstandinidou, Myrto & Nivolianitou, Zoe & Kefalogianni, Eirini & Caroni, Chrys, 2011. "In-depth analysis of the causal factors of incidents reported in the Greek petrochemical industry," Reliability Engineering and System Safety, Elsevier, vol. 96(11), pages 1448-1455.
    19. Rocco, Claudio M. & Hernandez-Perdomo, Elvis & Mun, Johnathan, 2021. "Assessing manufacturing flow lines under uncertainties in processing time: An application based on max-plus equations, multicriteria decisions, and global sensitivity analysis," International Journal of Production Economics, Elsevier, vol. 234(C).
    20. Zhou, Jianfeng & Reniers, Genserik, 2022. "Petri-net based cooperation modeling and time analysis of emergency response in the context of domino effect prevention in process industries," Reliability Engineering and System Safety, Elsevier, vol. 223(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:228:y:2022:i:c:s0951832022003738. 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.