Comparison of Artificial Neural Networks models with correlative works on undrained shear strength
Küçük Resim Yok
Tarih
2009
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
MAIK NAUKA/INTERPERIODICA/SPRINGER
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
In recent years, the Artificial Neural Network (ANN) modelling that has been used in the solution of the complex problems has gained an increasing interest in soil science. The ANN modelling is also getting more popular in soil mechanics applications. It is a preferable method among the other approaching methods because of having quick results in test phase in short time. This paper describes the ANN models for estimating undrained shear strength (S(u)) of cohesive soils from SPT (Standard Penetration Test) data with index properties in Turkey. The performance of the ANN models is investigated using different input variables such as measured N, corrected N (N(60)) value, natural water content (w(n)), liquid limit (w(L)), plasticity index (I(p)). In this study the ANN models are compared to empirical methods. The results indicate the superior performance of ANN models over the empirical methods.
Açıklama
Anahtar Kelimeler
Kaynak
EURASIAN SOIL SCIENCE
WoS Q Değeri
Q4
Scopus Q Değeri
Q2
Cilt
42
Sayı
13
