Cited by
Cited by
Methods used for the development of neural networks for the prediction of water resource variables in river systems: Current status and future directions
HR Maier, A Jain, GC Dandy, KP Sudheer
Environmental modelling & software 25 (8), 891-909, 2010
A neuro-fuzzy computing technique for modeling hydrological time series
PC Nayak, KP Sudheer, DM Rangan, KS Ramasastri
Journal of Hydrology 291 (1-2), 52-66, 2004
A data‐driven algorithm for constructing artificial neural network rainfall‐runoff models
KP Sudheer, AK Gosain, KS Ramasastri
Hydrological processes 16 (6), 1325-1330, 2002
Groundwater level forecasting in a shallow aquifer using artificial neural network approach
PC Nayak, YRS Rao, KP Sudheer
Water resources management 20, 77-90, 2006
Sensitivity and identifiability of stream flow generation parameters of the SWAT model
R Cibin, KP Sudheer, I Chaubey
Hydrological Processes: An International Journal 24 (9), 1133-1148, 2010
Estimating actual evapotranspiration from limited climatic data using neural computing technique
KP Sudheer, AK Gosain, KS Ramasastri
Journal of irrigation and drainage engineering 129 (3), 214-218, 2003
Short‐term flood forecasting with a neurofuzzy model
PC Nayak, KP Sudheer, DM Rangan, KS Ramasastri
Water Resources Research 41 (4), 2005
Rainfall‐runoff modelling using artificial neural networks: comparison of network types
AR Senthil Kumar, KP Sudheer, SK Jain, PK Agarwal
Hydrological Processes: An International Journal 19 (6), 1277-1291, 2005
Modelling evaporation using an artificial neural network algorithm
KP Sudheer, AK Gosain, D Mohana Rangan, SM Saheb
Hydrological Processes 16 (16), 3189-3202, 2002
Fuzzy computing based rainfall–runoff model for real time flood forecasting
PC Nayak, KP Sudheer, KS Ramasastri
Hydrological Processes: An International Journal 19 (4), 955-968, 2005
Identification of physical processes inherent in artificial neural network rainfall runoff models
A Jain, KP Sudheer, S Srinivasulu
Hydrological processes 18 (3), 571-581, 2004
Fitting of hydrologic models: a close look at the Nash–Sutcliffe index
SK Jain, KP Sudheer
Journal of hydrologic engineering 13 (10), 981-986, 2008
Artificial neural network modeling for groundwater level forecasting in a river island of eastern India
S Mohanty, MK Jha, A Kumar, KP Sudheer
Water resources management 24, 1845-1865, 2010
Radial basis function neural network for modeling rating curves
KP Sudheer, SK Jain
Journal of Hydrologic Engineering 8 (3), 161-164, 2003
Models for estimating evapotranspiration using artificial neural networks, and their physical interpretation
SK Jain, PC Nayak, KP Sudheer
Hydrological Processes: An International Journal 22 (13), 2225-2234, 2008
Ultimate bearing capacity prediction of shallow foundations on cohesionless soils using neurofuzzy models
D Padmini, K Ilamparuthi, KP Sudheer
Computers and Geotechnics 35 (1), 33-46, 2008
Explaining the internal behaviour of artificial neural network river flow models
KP Sudheer, A Jain
Hydrological Processes 18 (4), 833-844, 2004
Potential application of wavelet neural network ensemble to forecast streamflow for flood management
KS Kasiviswanathan, J He, KP Sudheer, JH Tay
Journal of hydrology 536, 161-173, 2016
Development and verification of a non-linear disaggregation method (NL-DisTrad) to downscale MODIS land surface temperature to the spatial scale of Landsat thermal data to …
VM Bindhu, B Narasimhan, KP Sudheer
Remote Sensing of Environment 135, 118-129, 2013
Improving peak flow estimates in artificial neural network river flow models
KP Sudheer, PC Nayak, KS Ramasastri
Hydrological Processes 17 (3), 677-686, 2003
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