Document Type : Original Research Paper

Authors

1 Faculty of Basic Science, Tarbiat Modares University, Theran, Iran

2 Faculty of Science, University of Esfahan, Esfahan, Iran.

3 Faculty of Basic Science, Tarbiat Modares University, Theran, Iran.

Abstract

The uniaxial compressive strength and modulus of deformability of intact rocks are highly important parameters for rock engineering and engineering geology projects. Because of the difficulty of  measuring these parameters and the need for laboratory equipments for their prediction, indirect methods are often used. In this study, some predictive models using regression analysis and fuzzy inference system have been developed for the Shales cropping out in the Shemshak formation in Siahbishe area. For this purpose, a series of easy measurable parameters such as density, porosity and point load index were applied. Both multiple regression analyses and the fuzzy inference system exhibited good performance in prediction of the uniaxial compressive strength and modulus of deformability. The variation of regression coefficient (R2), performance indices (VAF) and root mean square error (RMSE) were calculated as for the uniaxial compressive strength and the modulus of deformability obtained from the multiple regression model and the fuzzy inference system revealed that the prediction performances and accuracy of the fuzzy model are higher than those of multiple regression equations in prediction of uniaxial compressive strength and modulus of deformability.

Keywords

 
References
 
 
Alvarez Grima, M. & Babuska, R., 1999- Fuzzy model for the prediction of unconfined compressive strength of rock samples. Int. J. Rock Mech. Min. Sci 36, pp. 339–349.
Alvarez Grima, M., 2000 - Neuro-fuzzy modeling in engineering geology. A.A. Balkema, Rotterdam, 244 pp.
ASTM Standards, D 5731-95., 2000- Standard test method for determination of the point load strength index of rock, Annual Book of ASTM Standards  04.08., pp. 1442-1448.
Cargill, J. S. & Shakoor, A., 1990- Evaluation of empirical methods for measuring the uniaxial compressive strength, Int. J. Rock Mech. Min. Sci 27 (6),  pp. 495-503.
Den Hartog, M. H.&   Babuska, R., Deketh, H. J. R., Alvarez Grima, M.,Verhoef, P.N.W., Verbruggen, H.B., 1997- Knowledge-based fuzzy model for performance prediction of a rock-cutting trencher. International Journal of Approximate Reasoning 16, pp. 43–66.
Edet, A., 1992-  Physical properties and indirect estimation of microfractures using Nigerian carbonate rocks as examples. Engineering Geology 33, pp. 71–80.
Fahy,  M.  P.  & Guccione, M. ­J., 1979- Estimating strength of sandstone using petrographic thin-section data. Bulletin of the Association of Engineering Geologists XVII (4), pp. 467–485.
Finol, J., Guo, Y.­K. & Jing, X.­D., 2001-A rule based fuzzy model for the prediction of petrophysical rock parameters. Journal of  Petroleum Science and Engineering 29, pp. 97–113.
Gokceoglu, C., 2002- A fuzzy triangular chart to predict the uniaxial compressive strength of Ankara agglomerates from their petrographic composition. Engineering Geology 66, pp. 39–51.
Grasso, P., Xu, S.   &Mahtab, A., 1992- Problems and promises of index testing of rock. In: Tillerson, Waversik (Eds.), Rock Mechanics. Balkema, Rotterdam, pp. 879–888.
Gustafson, D. E., 1979 - Kessel WC. Fuzzy clustering with a fuzzy covariance matrix. In: Proc. IEEE CDC. San Diego, CA, pp.700-76
Howarth, D. F. & Rowlands, J. C., 1986- Development of an index to quantify rock texture for qualitative assessment of intact rock properties. Geotechnical Testing Journal 9, pp. 169–179.
Jang, J.­ S.­ R., 1993- ANFIS: Adaptive-network-based fuzzy inference systems, IEEE Transactions on Systems Man and Cybernetics 23 (3), pp. 665-685.
Lotfizadeh, A., 1973 - Outline of a new approach to the analysis of complex systems and decision processes, IEEE Transactions on Systems Man and Cybernetics 3 (1), pp. 28-44.
Mamdani, E. & Assilian, S., 1975 - An experiment in linguistic synthesis with a fuzzy logic controller, International Journal of Man-Machine Studies 7 (1), pp. 1-13.
Shakoor, A. & Bonelli, R. E., 1991- Relationship between petrographic characteristics, engineering Index properties and mechanical properties of selected sandstone. Bulletin of the Association of Engineering Geologists XXVIII (1), pp. 55–71.
Sugeno, M., 1985- Industrial applications of fuzzy control, New York, USA. Elsevier Science Pub. Co. 269 pp.
Ulusay, R.&  Tureli, K., Ider, M.­H., 1994- Prediction of engineering properties of a selected litharenite sandstone from its petrographic characteristics using correlation and multivariate statistical techniques, Eng. Geol 38, pp. 138-157.