Abstract
Abstract This paper focuses on the prediction of evapotranspiration on nursery area, in anticipative irrigation context management. The prediction of the plants water loose due to short terme fluctuations of the local climatic conditions is of a great importance, in the determination of the survival of the plants. A recurrent neural network model of evapotranspiration derived from Jordan approach is defined. The prediction are tested on steady state weather and on unsettled weather periods. The simulation results reported show the advantage of the model to predict evapotranspiration values when climatic conditions change, compared to the deterministic recurrent model. These simulations results encouraged the use of the neural predictive model in anticipated irrigation triggering
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
