Litcius/Paper detail

Modelling daily soil temperature by hydro-meteorological data at different depths using a novel data-intelligence model: deep echo state network model

Meysam Alizamir, Sungwon Kim, Mohammad Zounemat‐Kermani, Salim Heddam, Amin Hasanalipour Shahrabadi, Bahram Gharabaghi

2020Artificial Intelligence Review39 citationsDOI

Topics & Concepts

EvapotranspirationMean squared errorEnvironmental scienceRobustness (evolution)Echo state networkComputer scienceMachine learningHydrology (agriculture)Artificial neural networkRecurrent neural networkStatisticsMathematicsGeologyBiochemistryBiologyGeotechnical engineeringEcologyGeneChemistryNeural Networks and Reservoir ComputingHydrological Forecasting Using AIPlant Water Relations and Carbon Dynamics
Modelling daily soil temperature by hydro-meteorological data at different depths using a novel data-intelligence model: deep echo state network model | Litcius