A research team consisting of Assist Prof. Dr. Khaled Rasim Mahmoud, teaching in the Civil Engineering Department - College of Engineering - Anbar University, and Assistant Professor Dr. Nihad Baban Saleh, teaching in the Water Resources Engineering Department - Sulaymaniyah University, published scientific research in a solid international journal, which is KSCE Journal of Civil Engineering. This journal is one of the journals of the international publishing house Springer Nature and is classified under the Scopus Q2 index within the second quarter and Clarivate. It has an impact factor of 2.2 and a Cite Score = 3.9.

Research Title:

Using Artificial Neural Networks to predict the Unconfined Compressive Strength of Clayey Soils Stabilized by Various Stabilization Agents

The study aims to examine the possibility of applying artificial neural networks (ANNs) to build an effective prediction model for some geotechnical properties associated with clay soils stabilized using different stabilization materials. Four input variables including liquidity limit (LL), plasticity limit (PL), linear shrinkage limit (SL), and type of additives are used while the output is the unconfined compressive strength (UCS) of stabilized clay samples. Selected geotechnical properties can be determined in the laboratory on soil samples; However, these tests are time-consuming and expensive. Therefore, one model was developed to estimate UCS from texture parameters. ANNs models were developed and verified using a database of 74 cases of texture parameters of stabilized clay soils and based on the result of the study, the proposed ANNs model has good accuracy for predicting UCS of clay soils