It was 35 years ago since the first usage of Artificial Intelligence (AI) technique in
geotechnical engineering, during those years many (AI) techniques were developed based …

A comparison between deep learning and standalone models in predicting the compaction
parameters of soil is presented in this research. One hundred and ninety and fifty-three soil …

The aim of this study is to propose a reliable method to optimize the energy consumption of
buildings. Also, the most effective input parameters are defined which are used in the energy …

The deep soil mixing method (DSM) is known as a reliable and cost-efficient method of
ground improvement which has been studied in great detail for peat stabilisation. The …

Thermal conductivity is a key parameter characterizing heat and water transfer in soils. It is
difficult to measure thermal conductivity under freezing conditions. For this reason, some …

This study proposes a novel design to systematically optimize the parameters for the
adaptive neuro-fuzzy inference system (ANFIS) model using stochastic fractal search (SFS) …

Explosive loading in a confined internal environment is highly complex and is driven by
nonlinear physical processes associated with reflection and coalescence of multiple shock …

A new forecast method is proposed in order to improve the estimation accuracy of the
ultimate bearing capacity (UBC) of single driven piles. The performance of the adaptive …

A proper and reliable estimation of bearing capacity of thin-walled foundations is of
importance and necessary for accurate design of these structures. This study proposes a …

The use of cement as a soil stabilization agent is one of the common solutions to enhancing
the engineering properties of soil. However, the impact and cost of using cement have …