Professor Pijush Samui
Professor Pijush Samui
Professor, Dean(P &D), NIT Patna;Guest Professor, USTB Beijing; Title of Docent, Tampere University
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Cited by
Cited by
A novel deep learning neural network approach for predicting flash flood susceptibility: A case study at a high frequency tropical storm area
DT Bui, ND Hoang, F Martínez-Álvarez, PTT Ngo, PV Hoa, TD Pham, ...
Science of The Total Environment 701, 134413, 2020
A novel hybrid approach based on a swarm intelligence optimized extreme learning machine for flash flood susceptibility mapping
DT Bui, PTT Ngo, TD Pham, A Jaafari, NQ Minh, PV Hoa, P Samui
Catena 179, 184-196, 2019
Support vector machine applied to settlement of shallow foundations on cohesionless soils
P Samui
Computers and Geotechnics 35 (3), 419-427, 2008
Predicting concrete compressive strength using hybrid ensembling of surrogate machine learning models
PG Asteris, AD Skentou, A Bardhan, P Samui, K Pilakoutas
Cement and Concrete Research 145, 106449, 2021
Slope stability analysis: a support vector machine approach
P Samui
Environmental Geology 56, 255-267, 2008
Assessment of pile drivability using random forest regression and multivariate adaptive regression splines
W Zhang, C Wu, Y Li, L Wang, P Samui
Georisk: Assessment and Management of Risk for Engineered Systems and …, 2021
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, 329-342, 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, 1769-1784, 2016
Utilization of a least square support vector machine (LSSVM) for slope stability analysis
P Samui, DP Kothari
Scientia Iranica 18 (1), 53-58, 2011
Machine learning modelling for predicting soil liquefaction susceptibility
P Samui, TG Sitharam
Natural Hazards and Earth System Sciences 11 (1), 1-9, 2011
A novel hybrid swarm optimized multilayer neural network for spatial prediction of flash floods in tropical areas using sentinel-1 SAR imagery and geospatial data
PTT Ngo, ND Hoang, B Pradhan, QK Nguyen, XT Tran, QM Nguyen, ...
Sensors 18 (11), 3704, 2018
Effectiveness assessment of Keras based deep learning with different robust optimization algorithms for shallow landslide susceptibility mapping at tropical area
VH Nhu, ND Hoang, H Nguyen, PTT Ngo, TT Bui, PV Hoa, P Samui, ...
Catena 188, 104458, 2020
Spatial pattern analysis and prediction of forest fire using new machine learning approach of Multivariate Adaptive Regression Splines and Differential Flower Pollination …
DT Bui, ND Hoang, P Samui
Journal of environmental management 237, 476-487, 2019
Multivariate adaptive regression spline (Mars) for prediction of elastic modulus of jointed rock mass
P Samui
Geotechnical and Geological Engineering 31, 249-253, 2013
Compressive strength prediction of high-performance concrete using gradient tree boosting machine
MR Kaloop, D Kumar, P Samui, JW Hu, D Kim
Construction and Building Materials 264, 120198, 2020
Forecasting monthly precipitation using sequential modelling
D Kumar, A Singh, P Samui, RK Jha
Hydrological sciences journal 64 (6), 690-700, 2019
A novel technique based on the improved firefly algorithm coupled with extreme learning machine (ELM-IFF) for predicting the thermal conductivity of soil
N Kardani, A Bardhan, P Samui, M Nazem, A Zhou, DJ Armaghani
Engineering with Computers, 1-20, 2021
Modelling the energy performance of residential buildings using advanced computational frameworks based on RVM, GMDH, ANFIS-BBO and ANFIS-IPSO
N Kardani, A Bardhan, D Kim, P Samui, A Zhou
Journal of Building Engineering 35, 102105, 2021
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
Application of soft computing techniques for shallow foundation reliability in geotechnical engineering
R Ray, D Kumar, P Samui, LB Roy, ATC Goh, W Zhang
Geoscience Frontiers 12 (1), 375-383, 2021
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