An Example of Artificial Neural Network (ANN) Application for Indirect Estimation of Rock Parameters

Construction of an artificial neural network model for predicting the modulus of elasticity and unconned compressive strength is presented. Among other things, data found that the neural network is a sound approach for minimizing the uncertainties in soil engineering projects.

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Bibliographic Details
Published inRock mechanics and rock engineering Vol. 41; no. 5; pp. 781 - 795
Main Authors Yılmaz, I., Yuksek, A. G.
Format Journal Article
LanguageEnglish
Published Vienna Springer-Verlag 01.10.2008
Springer Nature B.V
Subjects
Civil Engineering
Earth and Environmental Science
Earth Sciences
Geological engineering
Geophysics/Geodesy
Neural networks
Regression analysis
Sedimentary geology
Shear strength
Soil engineering
Technical Note
Keywords: Artificial neural network, multiple regression, gypsum, elasticity modulus, unconfined compressive strength
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Summary:Construction of an artificial neural network model for predicting the modulus of elasticity and unconned compressive strength is presented. Among other things, data found that the neural network is a sound approach for minimizing the uncertainties in soil engineering projects.
Bibliography:ObjectType-Article-2
SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 23
ISSN:0723-2632
1434-453X
DOI:10.1007/s00603-007-0138-7