Erzin Y.2024-07-222024-07-222008http://akademikarsiv.cbu.edu.tr:4000/handle/123456789/18955Artificial neural networks (ANNs) are a new type of information processing system based on modeling the neural system of human brain. The prediction of swell pressures from easily determined soil properties, namely, initial dry density, initial water content, and plasticity index, have been investigated by using artificial neural networks. The results of the constant volume swell tests in oedometers (ASTM 1990), performed on statically compacted specimens of Bentonite-Kaolinite clay mixtures with varying soil properties, were trained in an ANNs program and the results were compared with the experimental values. It is observed that the experimental results coincided with ANNs results.EnglishBentoniteClayData processingGeomechanicsKaoliniteSoftware testingSoil mechanicsClay mixturesConstant volumesDry densityExperimental valuesHuman brainInformation processing systemsNeural systemsOedometersPlasticity indicesSoil propertySwell pressureSwell testNeural networksConference paper