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Intelligent Prediction of the Horizontal Deformation During the Excavation Process Based on Particle Swarm Optimisation and Support Vector Machine

Yù Zhang et al.

The Baltic Journal of Road and Bridge Engineering2025https://doi.org/10.7250/bjrbe.2025-20.657article
ABDC C
Weight
0.50

What the paper says

The reasonable selection of soil layer parameters relates to the accurate prediction of the horizontal deformation of the foundation pit, which is the main problem of highway tunnel pit design. The aim of this paper is to obtain suitable soil layer parameters for finite element simulation of highway tunnel based on the particle swarm optimisation (PSO) and support vector machine (SVM). First, considering the overfitting problem of SVM in the inversion of soil parameters, the PSO was used to improve the SVM model. Second, the PSO- SVM model was trained with 25 groups of elastic modulus as input values and deformation as output values. Then, according to the monitored deformation data, the soil parameters were inverted by PSO-SVM model. Finally, the inversion parameters were substituted into the finite element model to predict the horizontal deformation of the foundation pit. The results showed that based on the inversion parameters of PSO-SVM model, the finite element method had a good accuracy in predicting the horizontal deformation of the foundation pit. The average relative error between the predicted value and monitored value was 2.95%. Therefore, the application of the parameter inversion method based on PSO-SVM had a reference value for tunnel pit design.

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https://doi.org/https://doi.org/10.7250/bjrbe.2025-20.657

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@article{yù2025,
  title        = {{Intelligent Prediction of the Horizontal Deformation During the Excavation Process Based on Particle Swarm Optimisation and Support Vector Machine}},
  author       = {Yù Zhang et al.},
  journal      = {The Baltic Journal of Road and Bridge Engineering},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.7250/bjrbe.2025-20.657},
}

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Intelligent Prediction of the Horizontal Deformation During the Excavation Process Based on Particle Swarm Optimisation and Support Vector Machine

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.