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Prediction Method of Shield Tunneling Attitude Based on AWPSO-GRU Algorithm: Taking the Shanghai Suburban Railway Airport Connection Line as an Example
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Mei-heng ZHU1, Zhao-geng CHEN2, *, Dong-mei ZHANG2, 3, 4, Jun-hua GAO1, Zhong-kai HAUNG3
Science Technology and Engineering | 2025, 25(14) : 6062 - 6071
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Science Technology and Engineering | 2025, 25(14): 6062-6071
• Papers·Traffics and Transportations •
Prediction Method of Shield Tunneling Attitude Based on AWPSO-GRU Algorithm: Taking the Shanghai Suburban Railway Airport Connection Line as an Example
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Mei-heng ZHU1, Zhao-geng CHEN2, *, Dong-mei ZHANG2, 3, 4, Jun-hua GAO1, Zhong-kai HAUNG3
Affiliations
  • 1. Project Department of Shanghai Airport Connecting Line, CCCC Tunnel Engineering Bureau Co., Ltd.,Nanjing 211106, China
  • 2. Shanghai Research Institute for Intelligent Autonomous Systems, Tongji University, Shanghai 200092, China
  • 3. Department of Geotechnical Engineering, College of Civil Engineering, Tongji University, Shanghai 200092, China
  • 4. School of Civil Engineering, Qinghai University, Xining 810016, China
Published: 2025-05-18 doi: 10.12404/j.issn.1671-1815.2402821
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To solve the engineering problem of unclear standards and strong subjective experience when shield tunneling drivers set excavation parameters, which makes it difficult to control the shield tunneling attitude, an intelligent prediction model for shield tunneling attitude that considers the comprehensive effect of geological conditions, tunnel structure, and excavation parameters was proposed. Firstly, AWPSO (adaptive inertia weight particle swarm optimization) algorithm was established. Then, a shield attitude prediction model was constructed by combining GRU (gated recurrent unit) neural network, where the AWPSO algorithm was used to determine the optimal combination of hyperparameters in the GRU neural network. Finally, a case study was conducted to verify the on-site monitoring data between Zhangjiang Station and Resort Station on the Shanghai Suburban Railway Airport Connection Line. The results indicate that the proposed shield tunneling attitude prediction model based on AWPSO-GRU has high reliability and engineering practicality, which can provide reference and basis for setting construction parameters during shield tunneling.

shield tunnel  /  particle swarm optimization  /  adaptive inertia weight  /  gated recurrent unit  /  shield attitude prediction
Mei-heng ZHU, Zhao-geng CHEN, Dong-mei ZHANG, Jun-hua GAO, Zhong-kai HAUNG. Prediction Method of Shield Tunneling Attitude Based on AWPSO-GRU Algorithm: Taking the Shanghai Suburban Railway Airport Connection Line as an Example[J]. Science Technology and Engineering, 2025 , 25 (14) : 6062 -6071 . DOI: 10.12404/j.issn.1671-1815.2402821
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Year 2025 volume 25 Issue 14
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Article Info
doi: 10.12404/j.issn.1671-1815.2402821
  • Receive Date：2024-04-17
  • Online Date：2025-07-09
  • Published：2025-05-18
Article Data
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History
  • Received：2024-04-17
  • Revised：2025-02-13
Funding
Affiliations
    1. Project Department of Shanghai Airport Connecting Line, CCCC Tunnel Engineering Bureau Co., Ltd.,Nanjing 211106, China
    2. Shanghai Research Institute for Intelligent Autonomous Systems, Tongji University, Shanghai 200092, China
    3. Department of Geotechnical Engineering, College of Civil Engineering, Tongji University, Shanghai 200092, China
    4. School of Civil Engineering, Qinghai University, Xining 810016, China
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小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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