Prediction Technology of Ground Surface Settlement under the Pipe Jacking Consyruction Based on Intelligent Algorithm

DOI

10.2991/978-94-6463-658-1_72How to use a DOI?

Keywords

Intelligent algorithm; Prediction of surface settlement under pipe jacking; Genetic algorithm

Abstract

The ground settlement under pipe jacking is one of the key factors affecting construction safety and engineering quality. At present, domestic and foreign scholars have carried out a large number of studies on the prediction technology of surface settlement through pipe piercing. However, most of these studies are based on the simple combination of construction experience and prediction methods, and lack of systematic analysis and in-depth research on relevant influencing factors and parameters. Under this background, this paper discusses a prediction technology of surface settlement based on neural network, genetic algorithm and particle swarm algorithm. By combining relevant theoretical research and field monitoring data, the neural network model, genetic algorithm model, particle swarm algorithm model and improved BP neural network model are established, and the model is used to predict the surface settlement under the pipe top. The results show that the improved BP neural network model has higher prediction accuracy.

Copyright

© 2025 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Xiaojun Yang
AU  - Zhihua Zhang
AU  - Chen Yin
AU  - Xingtao Zhou
AU  - Wei Qin
PY  - 2025
DA  - 2025/03/03
TI  - Prediction Technology of Ground Surface Settlement under the Pipe Jacking Consyruction Based on Intelligent Algorithm
BT  - Proceedings of the 2024 10th International Conference on Architectural, Civil and Hydraulic Engineering (ICACHE 2024)
PB  - Atlantis Press
SP  - 711
EP  - 721
SN  - 2352-5401
UR  - https://doi.org/10.2991/978-94-6463-658-1_72
DO  - 10.2991/978-94-6463-658-1_72
ID  - Yang2025
ER  -