Professor Pijush Samui
Professor Pijush Samui
Associate Professor, NIT Patna
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TitleCited byYear
Support vector machine applied to settlement of shallow foundations on cohesionless soils
P Samui
Computers and Geotechnics 35 (3), 419-427, 2008
Slope stability analysis: a support vector machine approach
P Samui
Environmental Geology 56 (2), 255, 2008
Utilization of a least square support vector machine (LSSVM) for slope stability analysis
P Samui, DP Kothari
Scientia Iranica 18 (1), 53-58, 2011
Estimation of monthly evaporative loss using relevance vector machine, extreme learning machine and multivariate adaptive regression spline models
RC Deo, P Samui, D Kim
Stochastic Environmental Research and Risk Assessment 30 (6), 1769-1784, 2016
Multivariate adaptive regression spline (Mars) for prediction of elastic modulus of jointed rock mass
P Samui
Geotechnical and Geological Engineering 31 (1), 249-253, 2013
Application of artificial intelligence to maximum dry density and unconfined compressive strength of cement stabilized soil
SK Das, P Samui, AK Sabat
Geotechnical and Geological Engineering 29 (3), 329-342, 2011
OCR prediction using support vector machine based on piezocone data
P Samui, TG Sitharam, PU Kurup
Journal of Geotechnical and GeoEnvironmental engineering 134 (6), 894-898, 2008
Application of support vector machine and relevance vector machine to determine evaporative losses in reservoirs
P Samui, B Dixon
Hydrological Processes 26 (9), 1361-1369, 2012
Machine learning modelling for predicting soil liquefaction susceptibility.
P Samui, TG Sitharam, ME Contadakis
Natural Hazards & Earth System Sciences 11 (1), 2011
Prediction of swelling pressure of soil using artificial intelligence techniques
SK Das, P Samui, AK Sabat, TG Sitharam
Environmental Earth Sciences 61 (2), 393-403, 2010
Determination of ultimate capacity of driven piles in cohesionless soil: a multivariate adaptive regression spline approach
P Samui
International Journal for Numerical and Analytical Methods in Geomechanics …, 2012
Uplift capacity of suction caisson in clay using multivariate adaptive regression spline
P Samui, S Das, D Kim
Ocean Engineering 38 (17-18), 2123-2127, 2011
Stability determination for layered soil slopes using the upper bound limit analysis
J Kumar, P Samui
Geotechnical & Geological Engineering 24 (6), 1803, 2006
Application of least square support vector machine (LSSVM) for determination of evaporation losses in reservoirs
S Pijush
Engineering 2011, 2011
Seismic liquefaction potential assessment by using relevance vector machine
P Samui
Earthquake Engineering and Engineering Vibration 6 (4), 331-336, 2007
Prediction of field hydraulic conductivity of clay liners using an artificial neural network and support vector machine
SK Das, P Samui, AK Sabat
International Journal of Geomechanics 12 (5), 606-611, 2012
Prediction of friction capacity of driven piles in clay using the support vector machine
P Samui
Canadian Geotechnical Journal 45 (2), 288-295, 2008
Multivariate adaptive regression spline and least square support vector machine for prediction of undrained shear strength of clay
P Samui, P Kurup
International Journal of Applied Metaheuristic Computing (IJAMC) 3 (2), 33-42, 2012
Uplift capacity of suction caisson in clay using artificial intelligence techniques
PK Muduli, MR Das, P Samui, S Kumar Das
Marine Georesources & Geotechnology 31 (4), 375-390, 2013
Site characterization model using artificial neural network and kriging
P Samui, TG Sitharam
International Journal of Geomechanics 10 (5), 171-180, 2010
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