Measurement and modelling of the water requirement of some greenhouse crops with artificial neural networks and genetic algorithm
by Saeid Eslamian; Jahangir Abedi-Koupai; Mohammad Javad Zareian
International Journal of Hydrology Science and Technology (IJHST), Vol. 2, No. 3, 2012

Abstract: Crop evapotranspiration is the most important parameter for management of irrigation systems in greenhouses. This study was conducted to determine the evapotranspiration of cucumber, tomato and peppers, using micro-lysimeter during seven months in a greenhouse located in central region of Iran. Reference evapotranspiration estimated using drainage lysimeters and the water balance of soil micro-lysimeters was determined using the gravimetric method. To find the relationship between meteorological data and crops height with crops evapotranspiration, artificial neural networks (ANNs) and genetic algorithms-ANNs (GA-ANNs) were used. The results indicated that both models had a quite good agreement with the actual evapotranspiration of crops, but the GA-ANNs model will respond better than the ANNs model.

Online publication date: Sat, 16-Aug-2014

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