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[1]ZHANG Li,WU Jin-liang,YANG Guo-fan.Prediction Research for Crop Water Requirement Based on BP Neural Network in Donggang Irrigation District[J].Research of Soil and Water Conservation,2012,19(06):207-210,216.

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Prediction Research for Crop Water Requirement Based on BP Neural Network in Donggang Irrigation District

Research of Soil and Water Conservation[ISSN 1005-3409/CN 61-1272/P] Volume: 19 Number of periods: 2012 06 Page number: 207-210,216 Column: Public date: 2012-12-20

Title:: Prediction Research for Crop Water Requirement Based on BP Neural Network in Donggang Irrigation District

Author(s):: ZHANG Li^1,2, WU Jin-liang², YANG Guo-fan²; 1. College of Tourism and Geographical Science, Jilin Normal University, Siping, Jilin 136000, China;
2. College of Hydraulic Engineering, Shenyang Agricultural University, Shenyang 110866, China

Keywords:: reference crop evapotranspiration; Matlab; BP neural networks

CLC:: S274.4

DOI:: -

Abstract:: In order to guide agricultural production in Donggang region, the impact of different meteorological factors on reference crop evapotranspiration (ET₀) were analyzed. Using the neural network toolbox of Matlab software, a three-layer artificial neural network model was established to predict ET₀ according to the conventional meteorological data during maize growth and development period of year 1999 and 2000 in Donggang city. In this network, the input variables were daily net radiation, daily average relative humidity and daily average wind speed, and the output variable was ET₀ which was calculated by the Penman-Monteith formula. The results showed that: (1) the average relative error between prediction ET₀ values and target ET₀ values was 9%, when 11 neural nodes in the hidden layer was adopted, tansig function was chosen as transfer function and trainlm function was used to train the network, therefore, a 3-11-1 optimal network was determined; (2) the change tendency of the predicted values with BP-ET₀ model prediction and the target was the basic consistency.

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