State-of-the-Art Review of Machine Learning Applications in Constitutive Modeling of Soils
Article Properties
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LanguageEnglish
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DOI (url)
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Publication Date2021/01/05
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Indian UGC (journal)
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Refrences156
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Citations51
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Pin Zhang
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Zhen-Yu Yin
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Yin-Fu Jin
Journal Categories
Science
Mathematics
Science
Mathematics
Instruments and machines
Electronic computers
Computer science
Technology
Engineering (General)
Civil engineering (General)
Refrences
| Title | Journal | Journal Categories | Citations | Publication Date |
|---|---|---|---|---|
| Intelligent modelling of clay compressibility using hybrid meta-heuristic and machine learning algorithms | Geoscience Frontiers |
| 69 | 2021 |
An AI‐based model for describing cyclic characteristics of granular materials | International Journal for Numerical and Analytical Methods in Geomechanics |
| 57 | 2020 |
| Mechanism of Microstructural Variation Under Cyclic Shearing of Shantou Marine Clay: Experimental Investigation and Model Development | Geotechnical and Geological Engineering |
| 8 | 2019 |
| 10.1080/1064119X.2018.1534294 | 2019 | |||
| Asymptotic Expansion as Prior Knowledge in Deep Learning Method for High dimensional BSDEs | Asia-Pacific Financial Markets |
| 40 | 2019 |
Refrences Analysis
The category
Technology: Engineering (General). Civil engineering (General) 67
is the most frequently represented among the references in this article. It primarily includes studies from Computers and Geotechnics and International Journal for Numerical and Analytical Methods in Geomechanics. The chart below illustrates the number of referenced publications per year.
Refrences used by this article by year
Citations
| Title | Journal | Journal Categories | Citations | Publication Date |
|---|---|---|---|---|
Deep learning‐accelerated multiscale approach for granular material modeling | International Journal for Numerical and Analytical Methods in Geomechanics |
| 2024 | |
| Modeling the Mechanical Response of Cement-Admixed Clay Under Different Stress Paths Using Recurrent Neural Networks | International Journal of Geosynthetics and Ground Engineering |
| 2024 | |
| Tensor-based physics-encoded neural networks for modeling constitutive behavior of soil | Computers and Geotechnics |
| 2024 | |
| A combined machine learning/search algorithm-based method for the identification of constitutive parameters from laboratory tests and in-situ tests | Computers and Geotechnics |
| 2024 | |
| Test and prediction for the shear behavior of the sand–irregular concrete interface under constant and dynamic normal loading | Soil Dynamics and Earthquake Engineering |
| 2024 |
Citations Analysis
The category
Technology: Engineering (General). Civil engineering (General): Engineering geology. Rock mechanics. Soil mechanics. Underground construction 26
is the most commonly referenced area in studies that cite this article. The first research to cite this article was titled An intelligent procedure for updating deformation prediction of braced excavation in clay using gated recurrent unit neural networks and was published in 2021. The most recent citation comes from a 2024 study titled NorSand4AI: a comprehensive triaxial test simulation database for NorSand constitutive model materials. This article reached its peak citation in 2023, with 19 citations. It has been cited in 30 different journals, 20% of which are open access. Among related journals, the Computers and Geotechnics cited this research the most, with 6 citations. The chart below illustrates the annual citation trends for this article.