Open AccessPENDUGAAN FLUKS PANAS DAN EVAPOTRANSPIRASI DENGAN JARINGAN SYARAF TIRUAN
HEAT FLUX AND EVAPOTRANSPIRATION ESTIMATION USING ARTIFICIAL NEURAL NETWORK
HEAT FLUX AND EVAPOTRANSPIRATION ESTIMATION USING ARTIFICIAL NEURAL NETWORK
Author(s) -
Satyanto Krido Saptomo
Publication year - 2011
Publication title -
agromet
Language(s) - English
Resource type - Journals
eISSN - 2655-660X
pISSN - 0126-3633
DOI - 10.29244/j.agromet.25.1.24-28
Subject(s) - evapotranspiration , sensible heat , latent heat , artificial neural network , wind speed , heat flux , mathematics , environmental science , meteorology , thermodynamics , physics , computer science , heat transfer , artificial intelligence , ecology , biology
Artificial neural network (ANN) approach was used to model energy dissipation process into sensible heat and latent heat (evapotranspiration) fluxes. The ANN model has 5 inputs which are leaf temperature T l , air temperature T a , net radiation R n , wind speed u c and actual vapor pressure e a . Adjustment of ANN was conducted using back propagation technique, employing measurement data of input and output parameters of the ANN. The estimation results using the adjusted ANN shows its capability in resembling the heat dissipation process by giving outputs of sensible and latent heat fluxes closed to its respective measurement values as the measured input values are given. The ANN structure presented in this paper suits for modeling similar process over vegetated surfaces, but the adjusted parameters are unique. Therefore observation data set for each different vegetation and adjustment of ANN are required.