[1]姚亚夫,彭昊..一种基于径向基神经网络的组合预测模型[J].郑州大学学报(工学版),2008,29(03):137-140.[doi:10.3969/j.issn.1671-6833.2008.03.035]
　Yao Yafu,Peng Hao.A combinatorial predictive model based on a radial basis neural network[J].Journal of Zhengzhou University (Engineering Science),2008,29(03):137-140.[doi:10.3969/j.issn.1671-6833.2008.03.035]

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一种基于径向基神经网络的组合预测模型()

分享到：

《郑州大学学报(工学版)》[ISSN:1671-6833/CN:41-1339/T]

卷:

29卷

期数:

2008年03期

页码:

137-140

栏目:

出版日期:

1900-01-01

文章信息/Info

Title:

A combinatorial predictive model based on a radial basis neural network

作者:

姚亚夫; 彭昊.

中南大学,机电工程学院,湖南,长沙,410083, 中南大学,机电工程学院,湖南,长沙,410083

Author(s):

Yao Yafu; Peng Hao

关键词:

组合预测模型;  最近邻聚类算法;  径向基;  RBF神经网络;  交通流量

Keywords:

combinatorial predictive models;  nearest neighbor clustering algorithm;  Radial basis;  RBF neural networks;  Traffic flow

DOI:

10.3969/j.issn.1671-6833.2008.03.035

文献标志码:

A

摘要:

根据基于最近邻聚类算法(NNCA)的径向基(RBF)神经网络和自回归求和滑动平均(ARIMA)两种方法,建立了各自的单项预测子模型,并利用RBF神经网络对两个单项预测子模型结果进行组合预测,得到最终的预测值.将该模型应用于长沙市某路段的交通流量预测,实验结果证明了该预测模型的有效性,采用组合预测模型比单一预测模型的预测精度有了较大提高.

Abstract:

According to the Radial Basis (RBF) neural network and autoregressive sum sliding average (ARIMA) based on nearest neighbor clustering algorithm (NNCA), their respective single-term prediction submodels are established, and the RBF neural network is used to combine the results of the two single-term prediction submodels to obtain the final prediction value. The experimental results prove the effectiveness of the model by applying the model to the traffic flow prediction of a certain road section in Changsha, and the prediction accuracy of the combined prediction model is greatly improved compared with the single prediction model.

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