Evapotranspiration modeling using linear genetic programming technique

Journal of Irrigation and Drainage Engineering

Volumn 136, Issue 10, 2010, Pages 715-723

  Kisi, Ozgur ^a   Guven, Aytac ^a  

^a ERCIYES UNIVERSITY   (Turkey)

Author keywords

Evapotranspiration modeling; Linear genetic programming; Neural networks; Support vector regression

Indexed keywords

ABSOLUTE ERROR; AIR TEMPERATURE; ARTIFICIAL NEURAL NETWORK; CALIFORNIA; CLIMATIC DATA; COMPARISON RESULT; DETERMINATION COEFFICIENTS; EMPIRICAL MODEL; HARGREAVES; IRRIGATION MANAGEMENT; LINEAR GENETIC PROGRAMMING; PENMAN-MONTEITH EQUATIONS; REFERENCE EVAPOTRANSPIRATION; RELATIVE HUMIDITIES; RITCHIE; ROOT-MEAN SQUARE ERRORS; SUPPORT VECTOR REGRESSION; SUPPORT VECTOR REGRESSIONS; WIND SPEED; WINDSOR;

ATMOSPHERIC HUMIDITY; ERRORS; EVAPOTRANSPIRATION; NEURAL NETWORKS; REGRESSION ANALYSIS; SUN; WATER SUPPLY;

GENETIC PROGRAMMING;

ACCURACY ASSESSMENT; AIR TEMPERATURE; ARTIFICIAL NEURAL NETWORK; EVAPOTRANSPIRATION; GENETIC ALGORITHM; HYDROLOGICAL MODELING; LINEARITY; RELATIVE HUMIDITY; SOLAR RADIATION; VECTOR AUTOREGRESSION; WIND VELOCITY;

CALIFORNIA; UNITED STATES;

EID: 77956821935     PISSN: 07339437     EISSN: None     Source Type: Journal    
DOI: 10.1061/(ASCE)IR.1943-4774.0000244     Document Type: Article

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