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This paper presents an artificial neural network (ANN) model for predicting the bearing capacity of strip footings on multi-layered cohesive soils, addressing the inaccuracies of existing methods. The study compares predictions from multiple regression models and multi-layer perceptrons (MLPs) against traditional methods, demonstrating that ANNs provide more accurate results. The research employs numerical formulations of upper and lower bound methods to develop a meta-model that effectively predicts the ul
- Author
- Tamer Amari
- Language
- EN