Application of artificial intelligence-based single and hybrid models in predicting seepage and pore water pressure of dams: A state-of-the-art review
B Beiranvand, T Rajaee - Advances in Engineering Software, 2022 - Elsevier
Failure of earth dams is one of the major challenges of civil engineering, one of the main
causes of which is uncontrolled seepage from the core and foundation of the dam. The use …
causes of which is uncontrolled seepage from the core and foundation of the dam. The use …
A contemporary review on deep learning models for drought prediction
Deep learning models have been widely used in various applications, such as image and
speech recognition, natural language processing, and recently, in the field of drought …
speech recognition, natural language processing, and recently, in the field of drought …
Deep learning methods for time-dependent reliability analysis of reservoir slopes in spatially variable soils
Abstract The Three Gorges Reservoir Area (TGRA) is one of the most important landslide-
prone regions in China, and rational stability evaluation of reservoir slopes in it is of great …
prone regions in China, and rational stability evaluation of reservoir slopes in it is of great …
[HTML][HTML] Predicting triaxial compressive strength of high-temperature treated rock using machine learning techniques
The accurate prediction of the strength of rocks after high-temperature treatment is important
for the safety maintenance of rock in deep underground engineering. Five machine learning …
for the safety maintenance of rock in deep underground engineering. Five machine learning …
Machine learning models to predict the tunnel wall convergence
Deformation and damage of the rock mass induced by excavation operations can result in
the tunnel wall convergence. Accurate prediction of the convergence is crucial for ensuring …
the tunnel wall convergence. Accurate prediction of the convergence is crucial for ensuring …
Prediction of secant shear modulus and damping ratio for an extremely dilative silica sand based on machine learning techniques
A better understanding of soil response to dynamic loads, including earthquakes, can result
in safer designs that can reduce casualties. The damping ratio and shear modulus are …
in safer designs that can reduce casualties. The damping ratio and shear modulus are …
A novel whale optimization algorithm optimized XGBoost regression for estimating bearing capacity of concrete piles
This paper presents a hybrid model combining the extreme gradient boosting machine
(XGBoost) and the whale optimization algorithm (WOA) to predict the bearing capacity of …
(XGBoost) and the whale optimization algorithm (WOA) to predict the bearing capacity of …
Integrated parameter optimization approach: Just-in-time (JIT) operational control strategy for TBM tunnelling
X Li, S Zhao, Y Shen, G Li, H Zhu - Tunnelling and Underground Space …, 2023 - Elsevier
The timely and appropriate adjustment of operational control strategy is necessary for
efficient tunnelling and hazard prevention in tunnel boring machine (TBM) projects. Because …
efficient tunnelling and hazard prevention in tunnel boring machine (TBM) projects. Because …
Prediction of jacking force using PSO-BPNN and PSO-SVR algorithm in curved pipe roof
H Zhou, S Huang, P Zhang, B Ma, P Ma… - … and Underground Space …, 2023 - Elsevier
Jacking force prediction is essential for pipe jacking construction, especially when facing
randomness, uncertainty, and nonlinear conditions, which is a challenge for most analysis …
randomness, uncertainty, and nonlinear conditions, which is a challenge for most analysis …
Integrating ChatGPT, Bard, and leading-edge generative artificial intelligence in building and construction industry: applications, framework, challenges, and future …
The infusion of generative artificial intelligence (AI), as exemplified by models such as
ChatGPT and Bard is proving to be a revolutionary catalyst within the building and …
ChatGPT and Bard is proving to be a revolutionary catalyst within the building and …