Taesam Lee – författare
Visar alla böcker från författaren Taesam Lee. Handla med fri frakt och snabb leverans.
6 produkter
Statistical Downscaling for Hydrological and Environmental Applications
E-bok, 2018
2251 kr
Lägg i varukorg
Global climate change is typically understood and modeled using global climate models (GCMs), but the outputs of these models in terms of hydrological variables are only available on coarse or large spatial and time scales, while finer spatial and temporal resolutions are needed to reliably assess …
Statistical Downscaling for Hydrological and Environmental Applications
E-bok, 2018
2251 kr
Lägg i varukorg
Global climate change is typically understood and modeled using global climate models (GCMs), but the outputs of these models in terms of hydrological variables are only available on coarse or large spatial and time scales, while finer spatial and temporal resolutions are needed to reliably assess …
Statistical Downscaling for Hydrological and Environmental Applications
Inbunden, 2018
2134 kr
Lägg i varukorg
Global climate change is typically understood and modeled using global climate models (GCMs), but the outputs of these models in terms of hydrological variables are only available on coarse or large spatial and time scales, while finer spatial and temporal resolutions are needed to reliably assess …
Deep Learning for Hydrometeorology and Environmental Science
Av Taesam Lee, Vijay P. Singh m. fl.
Inbunden, 2021
1316 kr
Lägg i varukorg
This book provides a step-by-step methodology and derivation of deep learning algorithms as Long Short-Term Memory (LSTM) and Convolution Neural Network (CNN), especially for estimating parameters, with back-propagation as well as examples with real datasets of hydrometeorology (e.g. streamflow and …
Deep Learning for Hydrometeorology and Environmental Science
Av Kyung Hwa Cho, Vijay P. Singh m. fl.
E-bok, 2021
1785 kr
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This book provides a step-by-step methodology and derivation of deep learning algorithms as Long Short-Term Memory (LSTM) and Convolution Neural Network (CNN), especially for estimating parameters, with back-propagation as well as examples with real datasets of hydrometeorology (e.g. streamflow and …
Deep Learning for Hydrometeorology and Environmental Science
Av Taesam Lee, Vijay P. Singh m. fl.
Häftad, 2022
1316 kr
Lägg i varukorg
This book provides a step-by-step methodology and derivation of deep learning algorithms as Long Short-Term Memory (LSTM) and Convolution Neural Network (CNN), especially for estimating parameters, with back-propagation as well as examples with real datasets of hydrometeorology (e.g. streamflow and …
