摘要
文章提出一种基于小波神经网络的粮食产量预测模型。给出具体的网络学习算法,并结合算法对我国粮食产量进行预测。为验证模型有效性,进行了对比测试。分析结果表明,小波神经网络模型比传统的BP神经网络模型具有收敛速度快,预测精度高的特点。
This paper proposed a forecast model of grain output based on wavelet neural network.Besides,detail learning algorithm was presented and it was used in the forecast of China＇s grain output.To validate effectiveness of the model,the test data were input separately wavelet neural network and BP neural network.By comparative test,higher precision and speed were achieved by using the model based on wavelet neural network.
出处
《计算机与数字工程》
2010年第3期176-178,共3页
Computer & Digital Engineering
关键词
小波
神经网络
预测模型
wavelet
neural network
prediction model
