ArticleScientific reports2024
Research on prediction of surrounding rock deformation and optimization of construction parameters of high ground stress tunnel based on WOA-LSTM.
Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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3 citing papers in PubMed.
- Improving end-bearing capacity prediction of rock-socketed shafts using Gaussian-augmented optimized extreme gradient boosting models.Scientific reports · 2026Article
- Deep learning driven prediction and comparative study of surrounding rock deformation in high speed railway tunnels.Scientific reports · 2025Article
- An advanced CNN-attention model with IFTTA optimization for prediction air consumption of relay nozzles.Scientific reports · 2025Article
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3 authors.
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Abstract
To accurately understand the deformation behavior of surrounding rock in the jiugongshan No.2 high ground stress tunnel and optimize construction parameters for improved efficiency, on-site monitoring was used to gather data on rock deformation and initial support contact pressure. A WOA-LSTM regression prediction model was proposed, and excavation advance depth was optimized using numerical simulation. The WOA-LSTM regression prediction model demonstrated high accuracy in tunnel deformation monitoring. The absolute errors between predicted and actual values of tunnel settlement and convergence at various measurement points average 2.53
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