Estimation of Future Reference Crop Evapotranspiration using Artificial Neural Networks
نویسندگان
چکیده
منابع مشابه
Estimation of Reference Evapotranspiration Using Artificial Neural Network Models and the Hybrid Wavelet Neural Network
Estimation of evapotranspiration is essential for planning, designing and managing irrigation and drainage schemes, as well as water resources management. In this research, artificial neural networks, neural network wavelet model, multivariate regression and Hargreaves' empirical method were used to estimate reference evapotranspiration in order to determine the best model in terms of efficienc...
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nowadays artificial neural networks (anns) are being applied in several problems of water engineering where there is no clear relationship between effective parameters on the estimation of phenomenon. this research was used to measure aerodynamic data inside and outside greenhouse for estimating reference evapotranspiration in greenhouse by using anns. ann was used with perceptron multilayer st...
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Daily evapotranspiration (ET) rates are needed for irrigation scheduling. Owing to the difficulty of obtaining accurate field measurements, ET rates are commonly estimated from weather parameters. A few empirical or semi–empirical methods have been developed for assessing daily reference crop ET, which is converted to actual crop ET using crop coefficients. The FAO Penman–Monteith method, which...
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runoff estimation is one of the main challenges encountered in water and watershed management. spatial and temporal changes of factors which influence runoff due to het-erogeneity of the basins explain the complicacy of relations. artificial neural network (ann) is one of the intelligence techniques which is flexible and doesn’t call for any much physically complex processes. these networks can...
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ژورنال
عنوان ژورنال: Journal of The Korean Society of Agricultural Engineers
سال: 2010
ISSN: 1738-3692
DOI: 10.5389/ksae.2010.52.5.001