A new approach for classification of clayey soil: A case study for Adapazari region, Turkey

Abstract

Adapazari city is founded on very deep alluvial deposits which mainly consist of gravel, sand, silt, silty and clayey sands and clay. In this study, neural networks (NN) are used in the classification of clay samples existence in north of Adapazari. NN is a powerful data modeling tool capable of capturing and representing complex relationships between input and output. It has been used as alternative method in engineering analyses and estimations. In order to define general soil condition of Adapazari region, the NN model was trained and tested using liquid limit and plasticity index of clay samples obtained from drillings and laboratory works. By this developed of new NN model, the formula for Adapazari clays was found out and presented.