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

Expert Systems with Applications

Volumn 36, Issue 3 PART 2, 2009, Pages 6874-6878

  Kahraman, S ^a   Gunaydin, O ^a   Alber, M ^b   Fener, M ^a  

^a NIGDE UNIVERSITY   (Turkey)

^b RUHR UNIVERSITY BOCHUM   (Germany)

Author keywords

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

Indexed keywords

CORROSION; ELASTIC MODULI; NEURAL NETWORKS; REGRESSION ANALYSIS; ROCKS;

DEFORMABILITY PROPERTIES; FAULT BRECCIA; GEOMECHANICAL PROPERTIES; INDIRECT METHODS; PREDICTIVE MODELS; SMOOTH SPECIMENS; TEXTURAL PROPERTIES; UNIAXIAL COMPRESSIVE STRENGTH;

COMPRESSIVE STRENGTH;

EID: 58349084247     PISSN: 09574174     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.eswa.2008.08.002     Document Type: Article

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