Construction Of Intelligent Prediction System For Water Saving Irrigation

Drip irrigation is a kind of local irrigation.It is currently one of the most effective water-saving irrigation techniques which can improve the utilization ratio of agricultural water.Research on the soil moisture movement is the precondition of system design and also the basis of developing effective water-saving irrigation technologies.Crop irrigation water requirement of accurate prediction is an important guarantee for effective water saving.Water-saving irrigation has very important guiding meaning of sustainable agriculture.This thesis mainly introduces water-saving irrigation from the view of irrigation and irrigation forecast model.The main research contents are summarized as follows:1)The object of the research was dry red loam under the conditions of non-crop growth indoor.The soil content in the process of soil water movement was monitored continuously by soil moisture sensor under the conditions of single-point source drip irrigation.The drippers discharge,initial soil water content and dripper water on movement of soil moisture and water content distribution were mainly studied in the thesis.2)Adaptive partitioning method based on site percolation model was proposed.The soil moisture content irrigated area was judged by defining the connectivity indicators.The algorithm was simulated by the MATALB software to verify the effectiveness of the method.Finally it was used to the lawn,and the results showed the feasibility and the practicability of the algorithm.3)With greenhouse cucumber as the research object,the thesis built water demand prediction model based on GA-BP algorithm,and the prediction effect of the model was validated by test samples.The results showed that prediction accuracy of the model was high,so it ccould be applied to predict water demand of greenhouse cucumber.4)A new prediction system about the greenhouse cucumber was designed based on MATLAB GUI interface.The system had a friendly man-machine interface,and it could be convenient to predict water demand of greenhouse cucumber for user.