Modeling of soil shear strength using multiple linear regression (MLR) at Penang, Malaysia
Abstract
This paper presents the multiple linear regression (MLR) soil strength models developed from electrical resistivity and seismic refraction tomography. The multiple linear regression technique is used to estimate the value of dependent variables of soil strength based on the value of two independent variables, namely resistivity and velocity values. These parameters were regressed using regression statistics technique for generating multiple linear regression model. The analysed model results of MLR model which is based on estimation of model dependent parameters (resistivity and velocity) calculated for P-value at significance level of 0.05 is 0.01572 and 0.01163, for soil’s cohesion parameter and 0.01966 and 0.02534, for soil’s friction angle parameter. Two MLR model equations were developed from the statistical analysis. The forecast accuracy of the MLR model is conducted for verification on the second stage. Based on these statistical analysis results, a new soil’s strength model from geophysical data set for near surface study were developed. The soil’s strength models developed using MLR is reliable to image the subsurface in two-dimensional form, which covered more region compared to traditional method.
References
Alejano, L.R., Pons, B., Bastante, F. G., Alonso, E. & Stockhausen, H.W. 2007. Slope geometry design as a means for controlling rockfalls in quarries. International Journal of Rock Mechanics and Mining Sciences 44(6): 903-921.
Ali, A., Huang J., Lyamin, A.V., Sloan, S.W. & Cassidy, M.J. 2014. Boundary effects of rainfall-induced landslides. Computers and Geotechnics 61: 341-354.
Bery, A.A. & Ismail, N.E.H. 2018. Empirical correlation between electrical resistivity and engineering properties of soils. Soil Mechanics and Foundation Engineering 54(6): 425-429.
Bery, A.A. 2018. Development of soil electrical conductivity (SEC) modelling for slope assessment in Penang, Malaysia. Proceedings of EAGE-HAGI 1st Asia Pacific Meeting on Near Surface Geoscience and Engineering. Yogyakarta, Indonesia.
Bery, A.A. 2016. Slope monitoring study using soil mechanics properties and 4-D electrical resistivity tomography methods. Soil Mechanics and Foundation Engineering 53(1): 24-29.
Besalatpour, A.A., Ayoubi, S., Hajabbasi, M.A., Mosaddeghi, M.R. & Schulin, R. 2013. Estimating wet soil aggregate stability from easily available properties in a highly mountainous watershed. CATENA 111: 72-79.
Chand, R., Chandra, S., Rao, V.A., Singh, V.S. & Jain, S.C. 2004. Estimation of natural recharge and its dependency on sub-surface geoelectric parameters. Journal of Hydrology 299(1): 67-83.
Egbe, J.G., Ewa, D.E., Ubi, S.E., Ikwa, G.B. & Tumenayo, O. 2017. Application of multilinear regression analysis in modeling of soil properties for geotechnical civil engineering works in Calabar South. Nigerian Journal of Technology 36(4): 1059-1065.
Elaoud, A., Hassen, H.B., Salah, N.B., Masmoudi, A. & Chehaibi, S. 2017. Modeling of soil penetration resistance using multiple linear regression (MLR). Arabian Journal of Geoscience 10(20): 442.
Greenwood, J.R., Norris, J.E. & Wint, J. 2004. Assessing the contribution of vegetation to slope stability. Proceedings of the Institution of Civil Engineers - Geotechnical Engineering, 199-207.
Huang, A.-B., Lee, J.-T., Ho, Y.-T., Chiu, Y.-F. & Cheng, S.-H. 2012. Stability monitoring of rainfall-induced deep landslides through pore pressure profile measurements. Soils and Foundations 52(4): 737-747.
Israil M., al-hadithi M., Singhal D.C. and Kumar B. 2006. Groundwater-recharge estimation using a surface electrical resistivity method in the Himalayan foothill region, India. Hydrogeology Journal 14(1): 44-50.
Jung C., Lee Y., Cho Y. and Kim S. 2017. A study of spatial soil moisture estimation using a multiple linear regression model and MODIS land surface temperature data corrected by conditional merging. Remote Sensing 9(8): 870.
Kiu, Y.C., Saad, R., Saidin, M., Nordiana, M.M. and Bery, A.A. 2012. Characterization of Bukit Bunuh ground subsurface by 2D resistivity for meteorite impact study. Electronic Journal of Geotechnical Engineering 17(RS): 3575-3583.
Kong T.B. 1994. Engineering properties of granitic soils and rocks of Penang Island, Malaysia”, Geological Society of Malaysia 35: 69-77.
Okpoli, C.C. 2013. Sensitivity and resolution capacity of electrode configurations. International Journal of Geophysics 2013: 608037.
Loke, M.H. & Barker, R.D. 1996. Rapid least-squares inversion of apparent resistivity pseudosections by a quasi-Newton method. Geophysical Prospecting 44(1): 131-152.
Loke, M.H. 2014. Inversion and interpretation of multi-dimensional resistivity surveys. Geotomo Software, Malaysia.
Koutsoyiannis, A. 2001. Theory of Econometrics. Palgrave Macmillan Limited, New York.
Maslinda, U., Nordiana, M.M. & Bery, A.A. 2017. Porosity determination from 2-D resistivity method in studying the slope failures. AIP Conference Proceedings 1861: 030025.
Okpoli, C.C. 2013. Sensitivity and resolution capacity of electrode configurations. International Journal of Geophysics 2013: 608037.
Rahardjo, H., Nio, A.S., Leong, E.C. & Song, N.Y. 2010. Effect of groundwater table position and soil properties on stability of slope during rainfall. Journal of Geotechnical and Geoenvironmental Engineering 136(11): 1555-1564.
Smethurst, J.A., Clarke, D. & Powrie, W. 2006. Seasonal changes in pore water pressure in a grass covered cut slope in London Clay. Geotechnique 56(8): 523-537.
Suwa, H., Mizuno, T. & Ishii, T. 2010. Prediction of a landslide and analysis of slide motion with reference to the 2004 Ohto slide in Nara, Japan. Geomorphology 124(3-4): 157-163.
Suzuki, K. & Higashi, S. 2001. Groundwater flow after heavy rain in landslide-slope area from 2-D inversion of resistivity monitoring data. GEOPHYSICS 66(3): 733-743.
Take, W.A. & Bolton, M.D. 2004. Identification of seasonal slope behaviour mechanisms from centrifuge case studies. Proceedings of Advances in Geotechnical Engineering: The Skempton Conference, 992-1004.
Theil, H. 1958. Economic Forecast and Policy. North-Holland Publishing Company, Amsterdam.
Yilmaz, I. & Kaynar, O. 2011. Multiple regression, ANN (RBF, MLP) and ANFIS models for prediction of swell potential of clayey soils. Expert Systems with Application 38(5): 5958-5966.
Zhan, T.L.T., Ng, C.W.W. & Fredlund D.G. 2007. Field study of rainfall infiltration into a grassed unsaturated expansive soil slope. Canadian Geotechnical Journal 44(4): 392-408.
