基于RBF神经网络的CPI预测

CONSUMER PRICE INDEX PREDICTION BASED ON RBF NEURAL NETWORK

采用RBF神经网络的结构、特性和训练算法,根据CPI(消费者物价指数)与其影响因素之间存在的映射关系,应用神经网络建立了多因素非线性时间序列预测模型。最后通过仿真实验和研究,把RBF神经网络与传统的BP网络预测结果进行比较,结果证明,该模型的预测精确度更高,结果令人满意。

In the paper we adopted the structure,characteristics and learning algorithm of RBF neural network to have established a prediction model of multi-relative factors and non-linear time series using neural network based on the mapping relationship between CPI（consumer price index） and the influential factors on it.Finally,RBF neural network and traditional BP network were compared in their prediction results each other through simulation experiments and studies,the result showed that the former has higher predictive precision,the result achieved is satisfied.