Application of artificial neural network in estimating monthly time series reference evapotranspiration with minimum and maximum temperatures

Paddy and Water Environment

Volumn 9, Issue 2, 2011, Pages 207-220

  Jahanbani, Heerbod ^a   El Shafie, Ahmed Hussein ^b  

^a UNIVERSITY PUTRA MALAYSIA   (Malaysia)

^b UNIVERSITI KEBANGSAAN MALAYSIA   (Malaysia)

Author keywords

Evapotranspiration; Feed forward backpropagation; Rich and poor data

Indexed keywords

ACCURATE ESTIMATION; ACCURATE PERFORMANCE; ARTIFICIAL NEURAL NETWORK; BAYESIAN REGULATION; DAILY TEMPERATURES; DATA ANALYSIS; FEEDFORWARD BACKPROPAGATION; HARGREAVES; INPUT PATTERNS; MAXIMUM TEMPERATURE; MEAN ABSOLUTE ERROR; METEOROLOGICAL DATA; MODEL ACCURACY; PENMAN-MONTEITH; PREDICTION MODEL; REFERENCE EVAPOTRANSPIRATION; REGRESSION COEFFICIENT; RELATIVE ERRORS; RICH AND POOR DATA; STATISTICAL PERFORMANCE;

BACKPROPAGATION; CLIMATE CHANGE; DATA REDUCTION; EVAPOTRANSPIRATION; FORECASTING; MERCURY COMPOUNDS; METEOROLOGY; NEURAL NETWORKS; OPTIMIZATION; SUN; TIME SERIES; TIME SERIES ANALYSIS; WATER SUPPLY;

CLIMATE MODELS;

EID: 79955729635     PISSN: 16112490     EISSN: 16112504     Source Type: Journal    
DOI: 10.1007/s10333-010-0219-1     Document Type: Article

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