Artificial neural networks as a basis for new generation of rock failure criteria

International Journal of Rock Mechanics and Mining Sciences

Volumn 48, Issue 7, 2011, Pages 1153-1159

  Rafiai, Hosein ^a   Jafari, Ahmad ^a  

^a UNIVERSITY OF TEHRAN   (Iran)

Author keywords

Artificial neural network; Bieniawski Yudhbir criterion; Ductile failure; Hoek Brown criterion; Rock strength

Indexed keywords

COMPRESSIVE STRESS; FAILURE (MECHANICAL); MEAN SQUARE ERROR; NEURAL NETWORK MODELS; ROCKS; STATISTICAL TESTS;

BIENIAWSKI-YUDHBIR CRITERIA; DUCTILE FAILURES; FAILURE CRITERIA; HOEK-BROWN CRITERION; MAJOR PRINCIPAL STRESS; MINOR PRINCIPAL STRESS; ROCK STRENGTH; ROCK TYPES; TEST SETS; TRAINING SETS;

FORECASTING;

ACCURACY ASSESSMENT; ARTIFICIAL NEURAL NETWORK; BRITTLE DEFORMATION; DUCTILE DEFORMATION; FAILURE ANALYSIS; HOEK-BROWN CRITERION; LABORATORY METHOD; ROCK MECHANICS; TENSION; TRIAXIAL TEST; UNIAXIAL STRENGTH;

EID: 80053132990     PISSN: 13651609     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ijrmms.2011.06.001     Document Type: Article

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