Evaluating the strength and deformability properties of Misis fault breccia using artificial neural networks

Küçük Resim Yok

Tarih

2009

Dergi Başlığı

Dergi ISSN

Cilt Başlığı

Yayıncı

PERGAMON-ELSEVIER SCIENCE LTD

Erişim Hakkı

info:eu-repo/semantics/closedAccess

Özet

Since the preparation of smooth specimens from the fault breccias are usually difficult and expensive, the development of some predictive models for the geomechanical properties of fault breccias will be useful. In this study, artificial neural networks (ANNs) analysis was applied on the data pertaining to Misis fault breccia to develop some predictive models for the uniaxial compressive strength (UCS) and elastic modulus (E) from the indirect methods. The developed ANNs models were also compared with the regression models. As a result of ANNs analysis, very good models were derived for both UCS and E estimation. It was shown that ANNs models were more reliable than the regression models. Concluding remark is that UCS and E values of Misis fault breccia can reliably be estimated from the indirect methods using ANNs analysis. (c) 2008 Elsevier Ltd. All rights reserved.

Açıklama

Anahtar Kelimeler

Fault breccia, Uniaxial compressive strength, Elastic modulus, Physical and textural properties, Artificial neural networks

Kaynak

EXPERT SYSTEMS WITH APPLICATIONS

WoS Q Değeri

Q1

Scopus Q Değeri

Q1

Cilt

36

Sayı

3

Künye