Artificial neural networks versus gene expression programming for estimating reference evapotranspiration in arid climate

Agricultural Water Management

Volumn 163, Issue , 2016, Pages 110-124

  Yassin, Mohamed A ^a   Alazba, A A ^a   Mattar, Mohamed A ^a,b  

^a KING SAUD UNIVERSITY   (Saudi Arabia)

^b Agricultural Research Center   (Egypt)

Author keywords

Arid environments; Artificial intelligence; Penman Monteith; Reference evapotranspiration

Indexed keywords

ARTIFICIAL INTELLIGENCE; EVAPOTRANSPIRATION; GENES; MEAN SQUARE ERROR; METEOROLOGY; NEURAL NETWORKS;

ARID ENVIRONMENTS; DETERMINATION COEFFICIENTS; EXPLICIT EQUATIONS; GENE EXPRESSION PROGRAMMING; METEOROLOGICAL STATION; PENMAN MONTEITH; REFERENCE EVAPOTRANSPIRATION; ROOT MEAN SQUARE ERRORS;

GENE EXPRESSION;

ALGORITHM; ARID ENVIRONMENT; ARTIFICIAL INTELLIGENCE; ARTIFICIAL NEURAL NETWORK; DIURNAL VARIATION; EVAPOTRANSPIRATION; MODEL VALIDATION; PENMAN-MONTEITH EQUATION; REFERENCE SAMPLE;

EID: 84942693874     PISSN: 03783774     EISSN: 18732283     Source Type: Journal    
DOI: 10.1016/j.agwat.2015.09.009     Document Type: Article

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