Title of article :
Evapotranspiration Simulation by Soft Computing Methods
Author/Authors :
Honarbakhsh، A نويسنده , , Angabini، S نويسنده , , Kakaei Lafdani، E نويسنده ,
Issue Information :
روزنامه با شماره پیاپی 0 سال 2013
Pages :
6
From page :
1368
To page :
1373
Abstract :
ABSTRACT: Exact prediction of evapotranspiration is necessary for study, design and management of irrigation systems. In this research, the suitability of soft computing approaches namely, fuzzy rule base, fuzzy regression and artificial neural networks for estimation of daily evapotranspiration has been examined and the results are compared to real data measured by lysimeter on the basis of reference crop (grass). Using daily climatic data from Haji Abad station in Hormozgan, west of Iran, including maximum and minimum temperatures, maximum and minimum relative humidity, wind speed and sunny hours, evapotranspiration was predicted by soft computing methods. The predicted evapotranspiration values from fuzzy rule base, fuzzy linear regression and artificial neural networks show root mean square error (RMSE) of 0.75, 0.79 and 0.81 mm/day and coefficient of determination of (R2) of 0.90, 0.87 and 0.85, respectively. Therefore, fuzzy rule base approach was found to be the most appropriate method employed for estimating evapotranspiration.
Journal title :
International Journal of Agriculture and Crop Sciences(IJACS)
Serial Year :
2013
Journal title :
International Journal of Agriculture and Crop Sciences(IJACS)
Record number :
883984
Link To Document :
بازگشت