摘要
在灰色预测的基础上,引入BP神经网络模型,建立了GM(1,1)和BP神经网络组合模型。此组合模型兼有灰色预测和BP神经网络预测的优点,模型既克服了原始数据少,数据波动性大对预测精度的影响,也增强了预测的自适应性。实例证明了组合模型的预测精度高于单独的GM(1,1)模型,可以用于公路客运量预测。
Based on gray estimation, the BP neural network model is introduced to setup GM （1, 1 ） and BP neural network integration model. This model has combined the advantages of gray estimation and BP neural network estimation, it has overcomed the influence by little raw data and high data fluctuation to precision of estimation, and also it has enhanced the self- adaptability of estimation. Practical instance proves the estimation precision of combined model is higher than individual GM （ 1,1 ）, and can be used in road passenger tragic estimation.
出处
《公路交通技术》
2006年第2期110-113,共4页
Technology of Highway and Transport
