Prediction of elastic modulus of jointed rock mass using artificial neural networks

Geotechnical and Geological Engineering

Volumn 26, Issue 4, 2008, Pages 443-452

  Maji, Vidya Bhushan ^a   Sitharam, T G ^a  

^a INDIAN INSTITUTE OF SCIENCE   (India)

Author keywords

Back propagation; Joint factor; Jointed rock mass; Neural networks; Radial basis function

Indexed keywords

ARTIFICIAL INTELLIGENCE; BACKPROPAGATION; COMPRESSION TESTING; DATA COMPRESSION; ELASTIC MODULI; FEEDFORWARD NEURAL NETWORKS; FORECASTING; PARAMETER ESTIMATION; RADIAL BASIS FUNCTION NETWORKS; ROCK MECHANICS; ROCKS; VEGETATION;

ARTIFICIAL NEURAL NETWORK (ANN) MODELS; ARTIFICIAL NEURAL NETWORK (ANNS); BUSINESS MEDIA; CONFINING PRESSURES; DATA COLLECTED; FEED-FORWARD BACK-PROPAGATION; JOINT CONFIGURATIONS; JOINT PARAMETERS; JOINT PROPERTIES; JOINTED ROCK MASSES; MODULUS RATIOS; RADIAL-BASIS FUNCTION (RBF); SPRINGER (CO); TRIAXIAL COMPRESSION TEST (IGC: D6);

NEURAL NETWORKS;

ARTIFICIAL NEURAL NETWORK; BACK PROPAGATION; ELASTIC MODULUS; ROCK MASS RESPONSE; ROCK MECHANICS; TRIAXIAL TEST; UNIAXIAL TEST;

EID: 46949088613     PISSN: 09603182     EISSN: None     Source Type: Journal    
DOI: 10.1007/s10706-008-9180-9     Document Type: Article

References (17)

1. Arora VK (1987) Strength and deformation behavior of jointed rocks. Ph.D. Thesis, Indian Institute of Technology, Delhi
2. Brown ET, Trollope DH (1970) Strength of models of jointed rock. J Soil Mech Found Div ASCE 96(SM2):685-704
3. Cover TM (1965) Geometrical and statistical properties of system of linear inequalities with application in pattern recognition. IEEE Trans Electron Comput EC-14:326-334
4. Einstein HH, Hirscfeld RC (1973). Models studies in mechanics of jointed rocks. J Soil Mech Found Div ASCE 99:229-248
5. Haykin S (1994) Neural network (A Comprehensive Foundation) Addition Wesley Longman (Singapore) Pte. Ltd, Indian Branch Delhi
6. Hassoun MH (1995) Fundamentals of artificial neural networks. MIT Press, Cambridge
7. Jain AK, Mao J, Mohiuddin KM (1996) Artificial neural networks: A tutorial. IEEE Comput 29(3):31-44
8. Masters T (1994) Practical neural network recipes in C++. Academic Press, Boston
9. Mhasker HN (1996) Neural networks for optimal approximation of smooth analytical functions. Neural Comput 8:1731-1742
10. Niyogi P, Girosi F (1996) On the relationship between generalization error, hypothesis complexity and sample complexity for radial basis functions. Neural Comput 8:819-842
11. Ramamurthy T (1993) Strength and modulus responses of anisotropic rocks. In: Hudson JA (ed) Rock engineering, vol 1, no. 13, pp. 313-329
12. Ramamurthy T, Arora VK (1994) Strength predictions for jointed rocks in confined and unconfined states. Int J Rock Mech Min Sci Geomech Abstr 13(1):9-22
13. Roy N (1993) Engineering behavior of rock masses through study of jointed models. Ph.D. Thesis, Indian Institute of Technology, Delhi
14. Sitharam TG, Sridevi J, Shimizu N (2001) Practical equivalent continuum characterization of jointed rock masses. Int J Rock Mech Min Sci 38:437-448
15. Sridevi J (2000) Numerical modeling of jointed rocks. PhD Thesis, Department of Civil Engineering, IISc, Bangalore
16. Toll D (1996) Artificial intelligence applications in geotechnical engineering. Geotechnical system group. University of Durham, Durham
17. Yaji RK (1984) Shear strength and deformation of jointed rocks. Ph.D. thesis. Indian Institute of Technology, New Delhi