متابعة
Durga Lal Shrestha
Durga Lal Shrestha
Senior Research Scientist, CSIRO
بريد إلكتروني تم التحقق منه على csiro.au - الصفحة الرئيسية
عنوان
عدد مرات الاقتباسات
عدد مرات الاقتباسات
السنة
Machine learning approaches for estimation of prediction interval for the model output‏
DL Shrestha, DP Solomatine‏
Neural networks 19 (2), 225-235, 2006‏
4782006
AdaBoost. RT: a boosting algorithm for regression problems‏
DP Solomatine, DL Shrestha‏
2004 IEEE international joint conference on neural networks (IEEE Cat. No …, 2004‏
4362004
Experiments with AdaBoost. RT, an improved boosting scheme for regression‏
DL Shrestha, DP Solomatine‏
Neural computation 18 (7), 1678-1710, 2006‏
2942006
A novel method to estimate model uncertainty using machine learning techniques‏
DP Solomatine, DL Shrestha‏
Water Resources Research 45 (12), 2009‏
2852009
A log‐sinh transformation for data normalization and variance stabilization‏
QJ Wang, DL Shrestha, DE Robertson, P Pokhrel‏
Water Resources Research 48 (5), 2012‏
1712012
Post-processing rainfall forecasts from numerical weather prediction models for short-term streamflow forecasting‏
DE Robertson, DL Shrestha, QJ Wang‏
Hydrology and Earth System Sciences 17 (9), 3587-3603, 2013‏
1632013
A novel approach to parameter uncertainty analysis of hydrological models using neural networks‏
DL Shrestha, N Kayastha, DP Solomatine‏
Hydrology and Earth System Sciences 13 (7), 1235-1248, 2009‏
1392009
Evaluation of numerical weather prediction model precipitation forecasts for short-term streamflow forecasting purpose‏
DL Shrestha, DE Robertson, QJ Wang, TC Pagano, HAP Hapuarachchi‏
Hydrology and Earth System Sciences 17 (5), 1913-1931, 2013‏
1362013
Ensemble dressing for hydrological applications‏
TC Pagano, DL Shrestha, QJ Wang, D Robertson, P Hapuarachchi‏
Hydrological Processes 27 (1), 106-116, 2013‏
116*2013
Data‐driven approaches for estimating uncertainty in rainfall‐runoff modelling‏
DL Shrestha, DP Solomatine‏
International Journal of River Basin Management 6 (2), 109-122, 2008‏
942008
Instance‐based learning compared to other data‐driven methods in hydrological forecasting‏
DP Solomatine, M Maskey, DL Shrestha‏
Hydrological Processes: An International Journal 22 (2), 275-287, 2008‏
892008
Estimation of predictive hydrologic uncertainty using the quantile regression and UNEEC methods and their comparison on contrasting catchments‏
N Dogulu, P López López, DP Solomatine, AH Weerts, DL Shrestha‏
Hydrology and Earth System Sciences 19 (7), 3181-3201, 2015‏
842015
A System for Continuous Hydrological Ensemble Forecasting (SCHEF) to lead times of 9 days‏
JC Bennett, DE Robertson, DL Shrestha, QJ Wang, D Enever, ...‏
Journal of Hydrology 519, 2832-2846, 2014‏
782014
Improving precipitation forecasts by generating ensembles through postprocessing‏
DL Shrestha, DE Robertson, JC Bennett, QJ Wang‏
Monthly Weather Review 143 (9), 3642-3663, 2015‏
772015
Uncertainty analysis in rainfall-runoff modelling-application of machine learning techniques: UNESCO-IHE PhD thesis.‏
DL Shrestha‏
482010
Evaluation of ensemble precipitation forecasts generated through post-processing in a Canadian catchment‏
SK Jha, DL Shrestha, TA Stadnyk, P Coulibaly‏
Hydrology and Earth System Sciences 22 (3), 1957-1969, 2018‏
392018
Neural networks in reconstructing missing wave data in sedimentation modelling‏
B Bhattacharya, DL Shrestha, DP Solomatine‏
Proceedings of the XXXth IAHR Congress 500, 770-778, 2003‏
282003
Eager and lazy learning methods in the context of hydrologic forecasting‏
DP Solomatine, M Maskey, DL Shrestha‏
The 2006 IEEE International Joint Conference on Neural Network Proceedings …, 2006‏
172006
Encapsulation of parametric uncertainty statistics by various predictive machine learning models: MLUE method‏
DL Shrestha, N Kayastha, D Solomatine, R Price‏
Journal of Hydroinformatics 16 (1), 95-113, 2014‏
142014
Assessing model prediction limits using fuzzy clustering and machine learning‏
DL Shrestha, J Rodriguez, RK Price, DP Solomatine‏
Proc. 7th Int. Conf. On Hydroinformatics, 4-8, 2006‏
92006
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مقالات 1–20