Applied Mathematics and Nonlinear Sciences
Journal license

Journal

Applied Mathematics and Nonlinear Sciences


Volume
& Issue

Volume 8, Issue 1


Published
on

June 22, 2023


Pages

2607-2616


DOI

Article

BIM Model Design of Deep Foundation Pit Engineering Based on BP Network


Authors

Wei Chenghui Affiliation:
Chongqing Vocational College of Science and Creation, Yongchuan, Chongqing, 402160, China.
, Chen Hao Affiliation:
Chongqing Vocational College of Science and Creation, Yongchuan, Chongqing, 402160, China.
and Wu Di Affiliation:
Chongqing Vocational College of Science and Creation, Yongchuan, Chongqing, 402160, China.


Abstract

It is of great significance to predict the multistage deformation of the foundation pit. A new neural network method is proposed in this paper. The disadvantages of the BP neural network multistage forecast method are discussed. A multistage recursive neural network model for foundation deformation prediction is established. They are taking a deep foundation pit project in the soft soil area as an example. The multistage deformation prediction method is verified in this paper. This new detection technique is feasible. This method can also be used for multistage forecasting.


Keywords

Deep foundation pit, Recursive neural network, Multi-step deformation prediction, Engineering design, 92B20


Citation

Chenghui, W., Hao, C., & Di, W. (2023). BIM model design of deep foundation pit engineering based on BP network. Applied Mathematics and Nonlinear Sciences, 8(1), 2607–2616. https://doi.org/10.2478/amns.2023.1.00441

Published by: Engineering Journals

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