Classification of Layers Using Artificial Neural Networks in the Province of Kurdistan (Iran) - Semko Arefpanah; Alireza Sharafi; Alireza Gholamian (Tehnički Glasnik)
Artificial Neural Networks (ANN) is a field that combines science, technology, and ancient and modern knowledge. It has demonstrated the ability to resolve complex engineering issues beyond the computational capacity of conventional approaches and classical mathematics. ANN has applications in various fields, including computer science, engineering science, biology and medical science, and communication science. Neural networks are particularly useful in civil engineering, particularly in geotechnical problems, where soil heterogeneity and nonlinear behavior significantly impact geotechnical phenomena. Researchers have employed ANN to address various geotechnical engineering issues, including behavioral modeling, due to their potent abilities on nonlinear and multivariate problems. In this study, information from boreholes was used to collect and classify data to describe soil strata. The outputs of the neural network showed general consistency when compared to experimental borehole data, indicating its effectiveness in estimating changes in the soil layer. This was achieved by first presenting the network with information from various boreholes.