سال انتشار: ۱۳۸۶
محل انتشار: پنجمین کنفرانس بین المللی زلزله شناسی و مهندسی زلزله
تعداد صفحات: ۹
Ghateh – (M. Sc). International Institute of Earthquake Engineering and Seismology
Shafiee – (Ph. D). International Institute of Earthquake Engineering and Seismology
Over the last few years, the use of artificial neural networks (ANNs) has increased in many areas of engineering. In particular, ANNs have been applied to many geotechnical engineering problems and have demonstrated some degree of success. A review of the literature reveals that ANNs has been used successfully in pile capacity prediction, modeling soil behavior, liquefaction, etc. In this paper two MLP models with different architectures are utilized for predicting damping ratio, shear modulus and pore pressure of aggregate-clay mixtures. The reliability of the models is tested using cross validation technique. The data used for training the networks is based on the laboratory tests for determining the dynamic properties of aggregate-clay mixtures. Finally the importance of each input parameter is determined using Garson’s approach.