基于神经网络模型的降水量预测研究

Study on precipitation prediction based on neural network model

采用BP和Elman神经网络分别建立预测模型,并以盐城市大丰区连续27年的降水资料为实例对预测模型进行了具体的应用。结果表明:BP神经网络和Elman神经网络都可以有效预测降水量,但是BP神经网络模型预测精度要优于Elman神经网络模型,具有更高的稳定性和准确性。

BP neural network and Elman neural network were respectively used to establish the prediction model,which were applied to the precipitation data of Dafeng District in Yancheng City for 27 years continuously.The result showed that both BP neural network and Elman neural network could effectively predict the precipitation.However,the prediction accuracy of BP neural network model was better than Elman neural network model,and the former method did have higher stability and accuracy.