CAJ | 학술논문

　　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。
　　종전통적회색GM（1，N）모형출발，이용회색관련분석법학정상관인소적관련도，인입루적법상관이론，대GM（1，N）모형진행삼수변식，건립기다인소적루적GM（1，N）모의모형，재차기출상，충분이용최신신식，용신식사상건립신식루적GM (1，N)예측모형。장해모형분별응용도남방모성시급북경시도로교통조성적모의화예측상，결과표명，소건립적신식루적GM (1，N)모형적모의정도고，예측결과평균상대오차비GM（1，1）모형환저，예측효과호，예측치환표명，접하래량년내，조성치기본유지은정。
Based on the traditional grey GM (1, N) model, the grey correlation analysis was used to determine the relation of the related factors. With the theory related to accumulative methodology, the parameter identification of the grey GM (1, N) model was carried out. The multifactor grey GM (1, N) simulation model was built up. On this basis, using the latest information and new information idea, the grey GM(1,N) forecast model was established. This model was then applied to the simulation and forecast of the traffic noise of Beijing and a city in south China, respectively. The result shows that the simulation precision of the new-information accumulative grey GM (1, N) model is high. Its mean relative error of prediction is lower than that of the traditional grey GM (1, N). The prediction of traffic noise of the two cities shows that the noise value will basically remain stable in the next two years.