新息累积GM (1，N)模型在交通噪声预测中的应用

从传统的灰色GM （1， N）模型出发，利用灰色关联分析法确定相关因素的关联度，引入累积法相关理论，对GM （1， N）模型进行参数辨识，建立起多因素的累积GM （1， N）模拟模型，在此基础上，充分利用最新信息，用新息思想建立新息累积GM (1， N)预测模型。将该模型分别应用到南方某城市及北京市道路交通噪声的模拟和预测上，结果表明，所建立的新息累积GM (1， N)模型的模拟精度高，预测结果平均相对误差比GM （1， 1）模型还低，预测效果好，预测值还表明，接下来两年内，噪声值基本维持稳定。

Application of New-information Accumulative GM (1, N) Model to Traffic Noise Prediction

Based on the traditional grey GM (1,N) model, with the relational theory of accumulative methodology introduced in and the parameter of the grey GM(1,N) model identified, the multifactor grey GM(1,N) simulation model was built up. On this basis, take advantage of the latest information of data and use new information to establish the grey GM(1,N) forecast model. The model was applied on the simulation and forecast of the traffic noise and environment noise, respectively. The result showed that the simulation precision of the accumulative grey GM(1,N) model is high and the prediction precision of the new information accumulative grey GM(1,N) model is well. Besides, the prediction precision was lower than the GM(1,1) model.