35 Years of (AI) in geotechnical engineering: state of the art

AM Ebid - Geotechnical and Geological Engineering, 2021 - Springer
It was 35 years ago since the first usage of Artificial Intelligence (AI) technique in
geotechnical engineering, during those years many (AI) techniques were developed based …

State-of-the-art review of machine learning applications in constitutive modeling of soils

P Zhang, ZY Yin, YF Jin - Archives of Computational Methods in …, 2021 - Springer
Abstract Machine learning (ML) may provide a new methodology to directly learn from raw
data to develop constitutive models for soils by using pure mathematic skills. It has …

Patterns and driving factors of biomass carbon and soil organic carbon stock in the Indian Himalayan region

J Ahirwal, A Nath, B Brahma, S Deb, UK Sahoo… - Science of the Total …, 2021 - Elsevier
Tree-based ecosystems are critical to climate change mitigation. The study analysed carbon
(C) stock patterns and examined the importance of environmental variables in predicting …

Towards data-driven constitutive modelling for granular materials via micromechanics-informed deep learning

T Qu, S Di, YT Feng, M Wang, T Zhao - International Journal of Plasticity, 2021 - Elsevier
The analytical description of path-dependent elastic-plastic responses of a granular system
is highly complicated because of continuously evolving microstructures and strain …

Numerical study of the effects of groundwater drawdown on ground settlement for excavation in residual soils

ATC Goh, RH Zhang, W Wang, L Wang, HL Liu… - Acta Geotechnica, 2020 - Springer
For deep excavations in residual soils that are underlain by highly fissured or fractured
rocks, it is common to observe the drawdown of the groundwater table behind the …

Base resistance of super-large and long piles in soft soil: performance of artificial neural network model and field implications

TQ Huynh, TT Nguyen, H Nguyen - Acta Geotechnica, 2023 - Springer
This study aims to examine the performance of artificial neural network (ANN) model based
on 1137 datasets of super-large (1.0–2.5 m in equivalent diameter) and long (40.2–99 m) …

Recent advances and future challenges for artificial neural systems in geotechnical engineering applications

MA Shahin, MB Jaksa, HR Maier - Advances in Artificial Neural …, 2009 - Wiley Online Library
Artificial neural networks (ANNs) are a form of artificial intelligence that has proved to
provide a high level of competency in solving many complex engineering problems that are …

The prediction of the critical factor of safety of homogeneous finite slopes using neural networks and multiple regressions

Y Erzin, T Cetin - Computers & Geosciences, 2013 - Elsevier
This study deals with development of artificial neural network (ANN) and multiple regression
(MR) models that can be employed for estimating the critical factor of safety (Fs) value of …

Digital soil mapping using remote sensing indices, terrain attributes, and vegetation features in the rangelands of northeastern Iran

E Mahmoudabadi, A Karimi, GH Haghnia… - Environmental monitoring …, 2017 - Springer
Digital soil mapping has been introduced as a viable alternative to the traditional mapping
methods due to being fast and cost-effective. The objective of the present study was to …

ملخص

AJ Choobbasti, F Farrokhzad, A Barari - Arabian journal of geosciences, 2009 - Springer
ملخص دراسة إخفاقات التربة مواضيع تخص علم الأرض والهندسة. هذه الدراسة تحتاج إلى مجهودات
المهندسين في الجيولوجيا والمهندسين الجيوتقنيين. المهندس الجيوتقني يجب أن يهتم …