Application of Data Mining Techniques for the Development of New Rock Mechanics Constitutive Models

Author:

Miranda T.,Sousa L. R.,Ruggenthen W.,Sousa R. L.

Publisher

Springer Berlin Heidelberg

Reference5 articles.

1. Miranda, T.: Geomechanical parameters evaluation in underground structures. Artificial intelligence, Bayesian probabilities and inverse methods. PhD thesis. University of Minho, Guimarães, Portugal, 291p. (2007)

2. Miranda, T., Sousa, L.R.: Application of Data Mining techniques for the development of new geomechanical characterization models for rock masses. In: Sousa, Vargas, Fernandes, Azevedo (eds.) Innovative Numerical Modelling in Geomechanics, 20p. (2012)

3. Sousa, L.R., Miranda, T., Ruggenthen, W., Sousa, R.L.: Models for geomechanical characterization of the rock mass formations at DUSEL using Data Mining techniques. In: ARMA Symposium, Chicago, vol. 14 (2012)

4. Lima, C., Resende, E., Esteves, C., Neves, J.: Bemposta II Powerhouse Shaft. Geotechnical Characterization, Design and Construction. In: 12th Int. Congress on Rock Mechanics, Beijing, October 19-22, 6p. (2011)

5. McPherson, B., Elsworth, D., Fairhurst, C., Kelsler, S., Onstott, T., Roggenthen, W., Wang, H.: EarthLab: A subterranean laboratory and observatory to study microbial life, fluid flow, and rock deformation, A Report the National Science Foundation, NSF, Washington, DC, 60 (2003)

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