摘要
利用非线性回归、BP、RBF神经网络自适应学习法模型,对社会消费品总额进行了预测和研究,结果表明用RBF网络自适应学习法所建立的模型经过训练后,可得到较精确的预测结果,并具有较强的应用性。
The canting on the substantial evidence and predict research to the social total retail of consumer goods is studied by the nonlinear regression, BP and RBF neural network learning method. The result shows that after training the model established with RBF neural network can get more accurate predict result and have stronger adaptability.
出处
《电气传动自动化》
2006年第1期59-61,共3页
Electric Drive Automation
基金
安微省教育厅自然基金项目(2004kjo39)
关键词
RBF神经网络
自适应学习法
社会消费品总额
RBF neural network
self-adaptation performance of the algorithm
total retail of consumer goods
