References
- Cabalar, A. F., A. Cevik, and C. Gokceoglu. 2012. “Some Applications of Adaptive Neuro-Fuzzy Inference System (ANFIS) in Geotechnical Engineering.” Computers and Geotechnics 40: 14–33. doi:10.1016/j.compgeo.2011.09.008.
- Ching, J., -K.-K. Phoon, and Y.-C. Chen. 2010. “Reducing Shear Strength Uncertainties in Clays by Multivariate Correlations.” Canadian Geotechnical Journal 47: 16–33. doi:10.1139/T09-074.
- Ching, J., -K.-K. Phoon, and J.-W. Yu. 2013. “Linking Site Investigation Efforts to Final Design Savings with Simplified Reliability-Based Design Methods.” Journal of Geotechnical and Geoenvironmental Engineering 140: 04013032. doi:10.1061/(ASCE)GT.1943-5606.0001049.
- Jalalifar, H., S. Mojedifar, and A. Sahebi. 2014. “Prediction of Rock Mass Rating Using Fuzzy Logic and Multi-Variable RMR Regression Model.” International Journal of Mining Science and Technology 24: 237–244. doi:10.1016/j.ijmst.2014.01.015.
- Jang, J.-S. 1993. “ANFIS: Adaptive-Network-Based Fuzzy Inference System.” IEEE transactions on systems, man, and cybernetics 23: 665–685. doi:10.1109/21.256541.
- Jang, J. S. R., C. T. Sun, and E. Mizutani. 1997. “Neuro-Fuzzy and Soft Computing-a Computational Approach to Learning and Machine Intelligence [Book Review].” IEEE Transactions on automatic control 42 (10): 1482–1484. doi:10.1109/TAC.1997.633847.
- Jia, C., L. Wei, H. Wang, and J. Yang. 2015. “A Hybrid Model Based on Wavelet Decomposition-Reconstruction in Track Irregularity State Forecasting.” Mathematical Problems in Engineering. doi:10.1155/2015/548720.
- Lingwanda, M. I., S. Larsson, and D. L. Nyaoro. 2015. “Correlations of SPT, CPT and DPL Data for Sandy Soil in Tanzania.” Geotechnical and Geological Engineering 33: 1221–1233. doi:10.1007/s10706-015-9897-1.
- Momeni, M., A. Shafiee, M. Heidari, M. K. Jafari, and M. R. Mahdavifar. 2012. “Evaluation of Soil Collapse Potential in Regional Scale.” Natural hazards 64: 459–479. doi:10.1007/s11069-012-0252-z.
- Müller, R., S. Larsson, and J. Spross. 2013. “Extended Multivariate Approach for Uncertainty Reduction in The Assessment of Undrained Shear Strength in Clays.” Canadian Geotechnical Journal 51: 231–245. doi:10.1139/cgj-2012-0176.
- Robertson, P. (2012). “Interpretation of In-situ Tests-Some Insights, 5th JK Mitchell Lecture”, 4th International Conference on Site Characterization ISC-4, Porto de Galinhas, Pernambuco, Brazil.
- Rogers, J. D. 2006. “Subsurface Exploration Using the Standard Penetration Test and the Cone Penetrometer Test.” Environmental & Engineering Geoscience 12: 161–179. doi:10.2113/12.2.161.
- Stefanoff, G., G. Sanglerat, U. Bergdahl, and K. J. Melzer (1990). Dynamic Probing: International Reference Test Procedure: Proc 1st International Symposium on Penetration Testing, ISOPT-1, Orlando, USA. doi:10.1099/002212871362327.
- Stenzel, G., and K. Melzer. 1978. “Soil Investigations With Penetration Tests According to Din 4094.” Tiefbau 20: 3.
- Tarawneh, B. 2017. “Predicting Standard Penetration Test N-Value From Cone Penetration Test Data Using Artificial Neural Networks.” Geoscience Frontiers 8 (1): 199–204. doi:10.1016/j.gsf.2016.02.003.
- Yilmaz, I., and O. Kaynar. 2011. “Multiple Regression, ANN (RBF, MLP) and ANFIS Models for Prediction of The Swell Potential of Clayey Soils.” Expert Systems with Applications 38: 5958–5966. doi:10.1016/j.eswa.2010.11.027.