作物蒸发蒸腾量的人工神经网络模型研究

Study on Artificial Neural Network Model for Crop Evapotranspiration

采用盆栽试验,利用BP-人工神经网络模拟作物的蒸发蒸腾量,分别构建ET1(气象因子)、ET2(气象因子与播种天数)、ET3(气象因子、播种天数和含水率)3种人工神经网络模型,并将预测结果与称重法得到的实际值ET进行比较,结果表明,所构建的ET3模型的计算精度较高,是一种最优的计算作物蒸发蒸腾量的BP-人工神经网络模型。

Based on pot experiment,BP-artificial neural network was used to simulate crop evapotranspiration and construct 3 kinds of artificial neural network models as ET1（meteorological factors）,ET2（meteorological factors and sowing days） and ET3（meteorological factors,sowing days and water content）.And the prediction result was compared with actual value ET that was obtained by weighing method.The results showed that the constructed ET3 model had higher calculation precision and an optimum BP-artificial neural network model for calculating crop evapotranspiration.