[1] Fattahi, H. (2016). “Application of improved support vector regression model for prediction of deformation modulus of a rock mass”. Engineering with Computers, 32: 567-580. DOI: 10.1007/s00366- 016-0433- 6.
[2] Park, H. J., West, T. R., and Woo, L. (2005). “Probabelestic analysis of rock slope stability and random properties of discontinuity parameters, Interstate Highway 40,Western North Colorado”. International Journal of Rock Mechanics and Mining Sciences, 13: 135-148.
[3] Sari, M., Karpuz, C., and Ayday, C. (2010). “Estimating rock mass properties using Monte Carlo simulation: Ankara andesites”. Computers & Geosciences, 36: 959-969.
[4] Minaeian, B., and Ahangari, K. (2013). “Estimation of uniaxial compressive strength based on P-wave and Schmidt hammer rebound using statistical method”. Arabian Journal of Geosciences, 6: 1925- 1931.
[5] Alemdag, S., Gurocak, Z., and Gokceoglu, C. (2015). “A simple regression based approach to estimate deformation modulus of rock masses”. Journal of African Earth Sciences, 110: 75-80.
[6] Kavur, B., Cvitanovic, N. S., and Hrzenjak, P. (2015). “Comparison between plate jacking and large flat jack test results of rock mass deformation modulus”. International Journal of Rock Mechanics and Mining Sciences, 73: 102-114.
[7] Armaghani, D. J., Amin, M. A. M., Yagiz, S., Faradonbeh, R. S., and Abdullah, R. A. (2016). “Prediction of uniaxial compressive strength of granitic rocks by various nonlinear tools and comparison of their performances”. International Journal of Rock Mechanics and Mining Sciences, 85: 174-186.
[8] Feng, X., and Jimenez, R. (2015). “Estimation of deformation modulus of rock masses based on Bayesian model selection and Bayesian updating approach”. Engineering Geology, 199: 19-27.
[9] Ajalloeian, R., and Mohammadi, M. (2014). “Estimation of limestone rock mass deformation modulus using empirical equations”. Bulletin of Engineering Geology and the Environment, 73: 541-550.
[10] Nejati, H. R., Ghazvinian, A. H., Moosavi, S. A., and Sarfarazi, V. (2014). “On the use of the RMR system for estimation of rock mass deformation modulus”. Bulletin of Engineering Geology and the Environment, 73: 531-540.
[11] Hoek, E., Carranza-Torres, C. T., and Corkum, B. (2002). “Hoek-Brown failure criterion-2002 edition, In: Proceedings of the fifth North American rock mechanics symposium”. Toronto, Canada, 1: 267-273.
[12] Hoek, E., and Brown, E. T. (2018). “The Hoek-Brown failure criterion and GSI – 2018 edition”. Journal of Rock Mechanics and Geotechnical Engineering, 11(3): 445-463. DOI: https://doi.org/10.1016/j.jrmge.2018.08.001.
[13] ربیعی وزیری، م.، شفیعی، ش.، پناهی، م. ح.؛ 1394؛ "تحلیل سینماتیکی ریزش‌های سنگی به وسیله روش‌های احتمالاتی و با در نظر گرفتن قابلیت اعتماد (بررسی موردی: معدن شماره یک گل گهر)". نشریه زمین‌شناسی کاربردی پیشرفته، شماره 15، ص 67-74.
[14] Kim, K., and Gao, H. (1995). “Probabilistic approaches to estimating variation in the mechanical properties of rock masses”. International Journal of Rock Mechanics and Mining Sciences, 34: 111-120.
[15] Hoek, E. T. (1998). “Reliability of the Hoek–Brown estimates of rock mass properties and their impact on design”. International Journal of Rock Mechanics and Mining Science, 35: 63-68.
[16] Sari, M. (2009). “The stochastic assessment of strength and deformability characteristics for a pyroclastic rock mass”. International Journal of Rock Mechanics and Mining Sciences, 46: 613-626.
[17] Idris, M. A, Saiang, D., and Nordlund, E. (2011). “Numerical analyses of the effects of rock mass property variability on open slope stability”. The 45th US rock mechanics/geomechanics symposium, San Francisco, USA, American Rock Mechanics Association (AMRA), 1530-1540.
[18] Rezaei, M., Asadizadeh, M., Majdi, A., and Farouq Hossaini, M. (2015). “Prediction of representative deformation modulus of longwall panel roof rock strata using Mamdani fuzzy system”. International Journal of Mining Science and Technology, 25: 23-30. DOI: http://dx.doi.org/10.1016/j.ijmst.2014.11.007.
[19] Asrari, A. A., Shahriar, K., and Ataeepour, M. (2015). “The performance of ANFIS model for prediction of deformation modulus of rock mass”. Arabian Journal of Geosciences, 8: 357-365.
[20] Asadizadeh, M., and Farouq Hossaini, M. (2016). “Predicting rock mass deformation modulus by artificial intelligence approach based on dilatometer tests”. Arabian Journal of Geosciences, DOI: 10.1007/s12517-015-2189-5.
[21] Gholamnejad, J., Bahaaddini, H. R., and Rastegar, M. (2013). “Prediction of the deformation modulus of rock masses using Artificial Neural Networks and Regression methods”. Journal of Mining & Environment, 4(1): 35- 43.
[22] Tutmez, B., Kahraman, S., and Günaydin, O. (2007). “Multifactorial fuzzy approach to the sawability classification of building stones, Construction and Building Materials”. Construction and Building Materials, 21: 1672-1679.
[23] Ming-Wu, W., Chen, G. Y., and Jin, J. L. (2011). “Risk evaluation of surrounding rock stability based on stochastic simulation of multi-element connection number and triangular fuzzy numbers”. Chinese Journal of Geotechnical Engineering, 33: 643-647.
[24] عطایی، م.، 1385؛ "تصمیم گیری چند معیاره فازی". انتشارات دانشگاه صنعتی شاهرود، 341 صفحه.
[25] Juang, C. H., Jhi, Y. Y., and Lee, D. H. (1998). “Stability analysis of existing slopes considering uncertainty”. Engineering Geology, 49: 111-133.
[26] Dodagoudar, G. R. (2000). “Reliability analysis of slopes using fuzzy sets theory”. Computers and Geotechnics, 27: 101-115.
[27] Alvarez Grima, M. (1999). “Fuzzy model for prediction of unconfined compressive strength of rock samples”. International Journal of Rock Mechanics and Mining Science, 36: 339-349.
[28] Wieczorek, G. F., and works, C. O. (2000). “Debris flow and flooding-6hazards associated with the December 1999 storm in coastal venezuela and strategies for mitigation”.S. Geological Survey, Open File Report 01-0144, http://pubs.usgs.gov/of/2001/ofr-01-0144/.
)
