Predicting the Small Strain Shear Modulus of Sands and Sand-Fines Binary Mixtures Using Machine Learning Algorithms

•Several ANN-based and GP algorithms are developed for Gmax prediction.•Evolutionary algorithms are for sands and sand-fines binary mixtures.•Confinement, void ratio, uniformity coefficient, particle shape and fines content are adopted as inputs.•Validity of models is examined through various statistical indices and measurement criteria.•Proposed models are shown to be superior to all empirical correlations for Gmax estimation.