Application of artificial neural networks and multivariate statistics to predict UCS and E using physical properties of Asmari limestones

Prediction of engineering properties of rocks from microscopic data

(2012) Y. Ozcelik et al.   Arabian Journal of Geosciences

Estimation of uniaxial compressive strength based on P-wave and Schmidt hammer rebound using statistical method

(2011) Behnaz Minaeian et al.   Arabian Journal of Geosciences

P-wave velocity test for assessment of geotechnical properties of some rock materials

(2011) Saffet Yagiz   BULLETIN OF MATERIALS SCIENCE

The usability of Cerchar abrasivity index for the prediction of UCS and E of Misis Fault Breccia: Regression and artificial neural networks analysis

(2010) S. Kahraman et al.   EXPERT SYSTEMS WITH APPLICATIONS

Genetic programming approach for estimating the deformation modulus of rock mass using sensitivity analysis by neural network

(2010) Morteza Beiki et al.   INTERNATIONAL JOURNAL OF ROCK MECHANICS AND MINING SCIENCES

Evolving neural network using a genetic algorithm for predicting the deformation modulus of rock masses

(2009) Abbas Majdi et al.   INTERNATIONAL JOURNAL OF ROCK MECHANICS AND MINING SCIENCES

Predicting intact rock strength for mechanical excavation using multivariate statistics, artificial neural networks, and regression trees

(2008) Bulent Tiryaki   ENGINEERING GEOLOGY

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

(2008) S. Kahraman et al.   EXPERT SYSTEMS WITH APPLICATIONS