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Prediction for Surface Subsidence of Shield Construction in Water-Rich Sand Egg Stratum Based on Edge Intelligence

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Edge Computing and IoT: Systems, Management and Security (ICECI 2022)

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Abstract

The refinement and intelligent control of shield tunneling is the development trend of modern tunnel construction technology. In order to better predict and control the surface subsidence caused by shield excavation, this paper takes the shield construction of Luoyang Metro Line 2 from Longmen Station to Longmen Avenue Station as the background, and proposes a method based on edge intelligence for shield construction in water-rich sand egg strata. Methods for predicting land subsidence. First, low latency and faster data processing are achieved by collecting a large amount of data containing dynamic information about geological conditions and surrounding environments during the shield tunneling process; then using the iFogSim simulator to create different configurations; second, establishing support A surface subsidence model based on vector regression was established, and the model was deployed on the edge equipment; finally, the model was evaluated using the monitoring data of surface subsidence of the water-rich sand egg formation in Luoyang area. The research results show that the edge computing-based system has lower latency and higher processing speed than only deploying cloud data centers. After Pearson-related parameter tuning and model comparison training with Linear as the kernel function, the mean square error of the predicted value and the collected value of the surface subsidence is better than the other two kernel functions. The method proposed in this paper can provide real-time prediction service for large-scale surface subsidence prediction caused by shield construction, and is more practical.

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Acknowledgment

This work was supported in part by the Scientific research projects funded by the Department of education of Hunan Province (No. 21C0628, No. 20C1472 and No. 22C0497), the Huaihua University Double First-Class initiative Applied Characteristic Discipline of Control Science and Engineering (No. ZNKZN2021–10), the National Natural Science Foundation of China (No. 62172182), the Hunan Provincial Natural Science Foundation of China (No. 2020JJ4490), the Project of Hunan Provincial Social Science Foundation (NO. 21JD046), the Huaihua University Project (No. HHUY2019–25), the Philosophy and Social Science Achievement Evaluation Committee of Huaihua (No. HSP2022YB40) and the Science and Technology Innovation 2030 Special Project Sub-Topics (No. 2018AAA0102100).

Author information

Authors and Affiliations

  1. School of Computer and Artificial Intelligence, Huaihua University, Huaihua, 418000, China

    Yanxia Gao, Yiwen Liu, Chunqiao Mi, Pengju Tang & Yuanquan Shi

  2. Key Laboratory of Wuling-Mountain Health Big Data Intelligent Processing and Application in Hunan Province Universities, Huaihua, 418000, China

    Yanxia Gao, Yiwen Liu, Chunqiao Mi & Yuanquan Shi

  3. Key Laboratory of Intelligent Control Technology for Wuling-Mountain Ecological Agriculture in Hunan Province, Huaihua, 418000, China

    Yanxia Gao, Yiwen Liu, Chunqiao Mi & Yuanquan Shi

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  1. Yanxia Gao
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  3. Chunqiao Mi
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Correspondence to Yiwen Liu .

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Editors and Affiliations

  1. Hunan University, Changsha, China

    Zhu **ao

  2. Donghua University, Shanghai, China

    ** Zhao

  3. Hunan University, Changsha, China

    **ngxia Dai

  4. Hunan University, Changsha, China

    **mei Shu

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© 2023 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Gao, Y., Liu, Y., Mi, C., Tang, P., Shi, Y. (2023). Prediction for Surface Subsidence of Shield Construction in Water-Rich Sand Egg Stratum Based on Edge Intelligence. In: **ao, Z., Zhao, P., Dai, X., Shu, J. (eds) Edge Computing and IoT: Systems, Management and Security. ICECI 2022. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 478. Springer, Cham. https://doi.org/10.1007/978-3-031-28990-3_14

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  • DOI: https://doi.org/10.1007/978-3-031-28990-3_14

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  • Publisher Name: Springer, Cham

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