Estimation of soil compaction parameters by using statistical analyses and artificial neural networks
Küçük Resim Yok
Tarih
2009
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
SPRINGER
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
This study presents the application of different methods (simple-multiple analysis and artificial neural networks) for the estimation of the compaction parameters (maximum dry unit weight and optimum moisture content) from classification properties of the soils. Compaction parameters can only be defined experimentally by Proctor tests. The data collected from the dams in some areas of Nigde (Turkey) were used for the estimation of soil compaction parameters. Regression analysis and artificial neural network estimation indicated strong correlations (r (2) = 0.70-0.95) between the compaction parameters and soil classification properties. It has been shown that the correlation equations obtained as a result of regression analyses are in satisfactory agreement with the test results. It is recommended that the proposed correlations will be useful for a preliminary design of a project where there is a financial limitation and limited time.
Açıklama
Anahtar Kelimeler
Compaction parameters, Atterberg limits, Soil properties, Artificial neural networks, Correlation
Kaynak
ENVIRONMENTAL GEOLOGY
WoS Q Değeri
Q3
Scopus Q Değeri
N/A
Cilt
57
Sayı
1
