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A BP Neural Network Model for Apple Stem Flow Rate under Water Storage Pit Irrigation
Pages: 82-85+89
Year: Issue:  4
Journal: Water Saving Irrigation

Keyword:  water storage pit irrigationstem flow ratemeteorological factorsBP neural network;
Abstract: In order to provide a reliable basis for the development of the irrigation system of apple orchard under the condition of water storage pit irrigation,dwarf apple trees in Taigu County of Shanxi Province were taken as the research object.Through one-year experiment,a large amount of stem flow rate data and meteorological factors data were obtained,and a BP neural network model between meteorological factors and stem flow rate was established by MATLAB software.The result showed that,it was reasonable to use radiation intensity,relative humidity,soil temperature,temperature and wind speed as input parameters,and the BP neural network model was highly correlated,the relative errors between the measured value and the predicted value of the stem flow rate could be controlled below 5%.Therefore,it is feasible to predict the stem flow rate with the meteorological factors through the BP neural network.
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