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ESTIMATION OF EVAPOTRANSPIRATION FOR WHEAT CROP USING ARTIFICIAL NEURAL NETWORK
Computers in Agriculture and Natural Resources, 23-25 July 2006, Orlando Florida
The study has been undertaken to investigate the utility of artificial neural networks (ANNs) for comparison of daily reference evapotranspiration (ET0) estimated by Penman-Monteith (PM) method and that of estimated by ANNs during growing season of wheat crop. Feed forward network has been used for prediction of ET0 using resilient back-propagation method. For the purpose of the study, daily meteorological observations such as minimum and maximum temperature, minimum and maximum relativedoi:10.13031/2013.21891 fatcat:e6k4fiku4rbufb2ahtmpvhsl7i