In this work, the compressive strength of concrete made from recycled aggregate is studied
and an intelligent prediction is proposed by using a novel artificial neural network (ANN) …

This study investigates the applicability of two artificial intelligence (AI) techniques, namely,
the support vector regression (SVR) and artificial neural network (ANN), in prediction of the …

Support vector machine techniques (polynomial and radial basis function) and random
forest regression techniques have been used to predict erodibility of an unsaturated soil …

Sensitivity and error analyses and machine-based prediction have been conducted on the
erodibility response of erodible unsaturated soil (degree of saturation 60%) treated with …

Urbanization and associated infrastructure development keep developing along the globe in
today's reality. In this case, the utility of every single weak land (soft soils) in the city is …

To predict the undrained shear strength (S u) for the fine-grained soil has been following the
cone penetration test (CPT) and pore pressure (u) measurements, even though the …

Purpose: Application of deep neural networks (DNN) and ensemble of ANN with bagging for
estimating of factor of safety (FOS) of soil stability with a comparative performance analysis …

In order to further improve the construction quality of water conservancy projects under
different soil conditions and ensure the safety, stability, and durability of water conservancy …

Purpose: This article uses soft computing-based techniques to elaborate a study on the
prediction of the friction angle of clay. Design/methodology/approach: A total of 30 data …

Artificial neural networks (ANNs) are often used recently by researchers to solve complex
and nonlinear problems. Standard penetration test (SPT) and cone penetration test (CPT) …