Rock Mass Classification by Multivariate Statistical Techniques and Artificial Intelligence

This publication has 29 references indexed in Scilit:

• Evaluation of prediction capability, robustness, and sensitivity in non-linear landslide susceptibility models, Guantánamo, Cuba
  Computers & Geosciences, 2011
• A probabilistic systems methodology to analyze the importance of factors affecting the stability of rock slopes
  Engineering Geology, 2011
• Rock slope stability assessment through rock mass classification systems
  International Journal of Rock Mechanics and Mining Sciences, 2009
• A new approach for application of rock mass classification on rock slope stability assessment
  Engineering Geology, 2007
• A neuro-fuzzy model for modulus of deformation of jointed rock masses
  Computers and Geotechnics, 2004
• Prediction of strength properties of some schistose rocks from petrographic properties using artificial neural networks
  International Journal of Rock Mechanics and Mining Sciences, 2001
• Application of neural networks for the prediction of the unconfined compressive strength (UCS) from Equotip hardness
  International Journal of Rock Mechanics and Mining Sciences, 1999
• Advanced supervised learning in multi-layer perceptrons — From backpropagation to adaptive learning algorithms
  Computer Standards & Interfaces, 1994
• Engineering classification of rock masses for the design of tunnel support
  Rock Mechanics and Rock Engineering, 1974
• Engineering classification of jointed rock masses. discussions of paper by Z.T. Bieniawski, trans. s. afr. instn. civ. engrs. v15, n12, Dec. 1973, and authors reply
  International Journal of Rock Mechanics and Mining Sciences, 1974