What question did this study set out to answer?

Synthesize current artificial intelligence and deep learning methodologies for predicting the ultimate bearing capacity of foundation systems and evaluate barriers to their practical engineering implementation.

August 16, 2026BuildingsOpen Access

Artificial Intelligence and Deep Learning Models for Bearing Capacity Prediction of Foundation Systems: A State-of-the-Art Review

View Full Paper

Ask AI

Bookmark

Authors

ZAZulkifl AhmedNortheastern University FAFahad AlshawmarQassim University

Discussion

Member takes

Implication

Systematic review demonstrates superior accuracy of deep learning for foundation bearing capacity prediction, indicating the need for robust field validation and physics-informed models.

Key Points

Synthesize current artificial intelligence and deep learning methodologies for predicting the ultimate bearing capacity of foundation systems and evaluate barriers to their practical engineering implementation.
Reviewed major AI and deep learning architectures, including ANNs, DNNs, CNNs, LSTMs, Transformers, GNNs, and physics-informed frameworks, across shallow, deep, and pile foundation applications.
Assessed integration strategies coupling machine learning with numerical techniques such as the finite element method (FEM) and finite element limit analysis (FELA).
AI and deep learning models consistently achieve lower prediction errors compared to traditional empirical, numerical, and standard machine learning approaches within benchmark datasets.
High reported performance frequently stems from interpolation within controlled laboratory or synthetic data rather than validated generalization to independent field conditions.
Widespread engineering adoption remains constrained by data scarcity, lack of external multi-site validation, limited model interpretability, and insufficient uncertainty quantification.

Cite This Study

Ahmed et al. (2026) studied this question.

synapsesocial.com/papers/6a8179bcf2fb91fc834ad0db https://doi.org/10.3390/buildings16163232

View Full Paper

Ask AI

Bookmark

Implication

Systematic review demonstrates superior accuracy of deep learning for foundation bearing capacity prediction, indicating the need for robust field validation and physics-informed models.

Artificial Intelligence and Deep Learning Models for Bearing Capacity Prediction of Foundation Systems: A State-of-the-Art Review

Discussion

Member takes

Implication

Key Points

Cite This Study

Artificial Intelligence and Deep Learning Models for Bearing Capacity Prediction of Foundation Systems: A State-of-the-Art Review

Discussion

Member takes

Implication

Key Points

Cite This Study

Also Consider

Also Consider