Prediction of stratum deformation during the excavation of a foundation pit in composite formation based on the artificial bee colony-back-propagation model

被引：27

作者：

Feng, Tugen ^{[1
]}

Wang, Chaoran ^{[1
]}

Zhang, Jian ^{[1
]}

Zhou, Kun ^{[1
]}

Qiao, Guangxuan ^{[1
]}

机构：

[1] Hohai Univ, Key Lab Minist Educ Geomech & Embankment Engn, Nanjing, Peoples R China

来源：

ENGINEERING OPTIMIZATION | 2022年 / 54卷 / 07期

基金：

中国国家自然科学基金;

关键词：

Composite formation; foundation pit deformation prediction; artificial bee colony algorithm; BP neural network; grey relational analysis; NEURAL-NETWORK; SETTLEMENT; OPTIMIZATION; PARAMETERS; ALGORITHM;

D O I：

10.1080/0305215X.2021.1919100

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

A method for predicting deformation during the excavation of a foundation pit in composite formation is proposed. The artificial bee colony algorithm (ABC) is introduced to optimize the back-propagation (BP) neural network with the input variables filtered. This method is applied to predict the deformation of a foundation pit project. The prediction results are verified by comparing the results with those of other neural network models. The results indicate that the depth of excavation, speed of excavation, friction angle in the soil, gravity, elastic modulus and number of internal support layers are the main factors affecting the deformation of the soil layer around the foundation pit. The ABC algorithm is capable of searching for better solutions of initial weights and thresholds. The ABC-BP model with a 6-12-2 network structure has high prediction accuracy and the best generalization ability.

引用

页码：1217 / 1235

页数：19

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