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
Short‐term flood forecasting with a neurofuzzy model
PC Nayak, KP Sudheer, DM Rangan, KS Ramasastri
Water Resources Research 41 (4), 2005
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
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
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
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
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
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
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
Radial basis function neural network for modeling rating curves
KP Sudheer, SK Jain
Journal of Hydrologic Engineering 8 (3), 161-164, 2003
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
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
Explaining the internal behaviour of artificial neural network river flow models
KP Sudheer, A Jain
Hydrological Processes 18 (4), 833-844, 2004
An improved bias correction method of daily rainfall data using a sliding window technique for climate change impact assessment
PS Smitha, B Narasimhan, KP Sudheer, H Annamalai
Journal of Hydrology 556, 100-118, 2018
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