Physics-Informed neural network solver for numerical analysis in geoengineering

XX Chen, P Zhang, ZY Yin - … of Risk for Engineered Systems and …, 2024 - Taylor & Francis
Engineering-scale problems generally can be described by partial differential equations
(PDEs) or ordinary differential equations (ODEs). Analytical, semi-analytical and numerical …

Modeling the mechanical response of cement-admixed clay under different stress paths using recurrent neural networks

C Phutthananon, P Ratanakijkul, S Youwai… - International Journal of …, 2024 - Springer
Cement–admixed clay (CAC) is a widely-used soil stabilization technique for enhancing the
strength and stiffness of soft clay. However, the stress–strain behavior of CAC is complex …

Data-and experience-driven neural networks for long-term settlement prediction of tunnel

DM Zhang, XY Guo, YM Shen, WD Zhou… - … and Underground Space …, 2024 - Elsevier
In recent years, machine learning methods have been widely used to predict the long-term
settlement of tunnels. However, data-driven models for long-term settlement prediction often …

Time-series forecasting of consolidation settlement using LSTM network

S Hong, SJ Ko, SI Woo, TY Kwak, SR Kim - Applied Intelligence, 2024 - Springer
Consolidation settlement refers to the deformation of soil due to external forces resulting in a
reduction in the soil volume, posing a significant challenge for construction on soft ground …

Artificial Intelligence and Deep Learning in Civil Engineering

A Ocak, SM Nigdeli, G Bekdaş, Ü Işıkdağ - Hybrid Metaheuristics in …, 2023 - Springer
Artificial intelligence is a variety of software developed that imitates the human brain to
perform the tasks that the human brain can do. Aiming to minimize human intervention, this …

Prediction of airport runway settlement using an integrated SBAS-InSAR and BP-EnKF approach

SH Xiong, ZP Wang, G Li, MJ Skibniewski, ZS Chen - Information Sciences, 2024 - Elsevier
The prediction of surface settlement occupies a crucial role in achieving effective
catastrophe prevention and mitigation, as well as facilitating the maintenance of airport …

[HTML][HTML] Application of Deep Learning Algorithms for Predicting Consolidation Settlement

S Hong, MH Lee, BS Yoo, TY Kwak, SR Kim - KSCE Journal of Civil …, 2025 - Elsevier
Significant amount of consolidation settlement can occur in construction sites with soft clayey
soil deposits. Accurate prediction is important to prevent serious issues, such as tilting and …

Prediction of Buildings' Settlements Induced by Deep Foundation Pit Construction Based on LSTM-RA-ANN

T Hu, J Xu - Applied Sciences, 2024 - mdpi.com
In view of the shortcomings of existing methods for predicting the settlement of surrounding
buildings caused by deep foundation pit construction, this study uses the monitoring data of …

[HTML][HTML] Monitoring Data Fusion Model for Subsoil Layer Deformation Prediction

H Wu, Y Wu, J Liu, L Zhang, Y Zhu, C Liang - Buildings, 2024 - mdpi.com
Predicting soil deformation is critical for the success of building construction projects. The
traditional methods used for this task, which rely on theoretical calculations and numerical …

연약지반침하예측을위한딥러닝및계측기반기법의예측정확도비교

홍성호, 곽태영, 우상인, 김성렬 - 한국지반공학회논문집, 2024 - dbpia.co.kr
대심도 연약지반에 선행재하 공법을 적용하는 경우 재하토 제거 시점을 예측하고 잔류침하량을
최소화하기 위해 연약지반의 침하거동을 정밀히 예측하는 것이 중요하다. 국내에서는 …