Neural network approach to reference evapotranspiration modeling from limited climatic data in arid regions

International Journal of Biometeorology

Volumn 56, Issue 5, 2012, Pages 831-841

  Laaboudi, Abdelkader ^a   Mouhouche, Brahim ^b   Draoui, Belkacem ^c  

^a Algerian Institute for Research in Agronomy   (Algeria)

^b National Agronomic Institute of El Harrach   (Algeria)

^c UNIVERSITY OF BECHAR   (Algeria)

Author keywords

Incomplete meteorological parameters; Limited water resources; Network architecture; Overfitting; Performance criteria; Reference evapotranspiration

Indexed keywords

ALGERIA; ARTICLE; ARTIFICIAL NEURAL NETWORK; CROP; DESERT CLIMATE; EVAPOTRANSPIRATION; HUMIDITY; PHYSIOLOGY; SUNLIGHT; TEMPERATURE; THEORETICAL MODEL; VAPOR PRESSURE; WIND;

ALGERIA; CROPS, AGRICULTURAL; DESERT CLIMATE; HUMIDITY; MODELS, THEORETICAL; NEURAL NETWORKS (COMPUTER); PLANT TRANSPIRATION; SUNLIGHT; TEMPERATURE; VAPOR PRESSURE; WIND;

EID: 84865618995     PISSN: 00207128     EISSN: None     Source Type: Journal    
DOI: 10.1007/s00484-011-0485-7     Document Type: Article

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