基于灰色回归组合模型的交通量预测研究  

Forecast of Traffic Volume Based on the Grey Regression Combined Model

作　　者：李大明[1] LI Daming(Liangyungang Road Administration Division,Lianyungang Jiangsu 222000)

机构地区：[1]连云港市公路管理处,江苏连云港222000

出　　处：《智能建筑与工程机械》2021年第3期114-116,共3页Intelligent Building and Construction Machinery

摘　　要：交通量预测作为公路可行性研究的核心内容,对其进行精准预测是对交通运输规划与管理研究的基础。交通运输问题随着车辆的增多变得日益复杂,故交通量预测逐渐变成研究的热点问题。本文结合智能计算、回归分析及灰色模型等理论,通过优化GM(1,1)模型,提出合理权重,结合回归模型和优化后的GM(1,1)模型,构建了优化的交通量组合预测模型。最后,经过滦马高速实际数据的检验,验证了该模型能够有效提高交通量短时预测精度。Traffic forecasting and accurate forecasting are central to highway feasibility studies and have important implications for traffic planning and management research.As the number of vehicles increases;transportation issues become more complex.A hot issue that theoretical researchers are concerned about is traffic forecasting,as traffic problems become more complex and the number of vehicles continues to grow.In this article,when optimizing a GM(1,1)model using regression analysis and gray model theory,we first combine intelligent calculations.Reasonable weights can be obtained by combining the regression model with the optimized GM(1,1)model.The establishment of a combination prediction model for linear traffic volume is mainly based on the gray model and the regression model.The actual data testing is mainly done on the Lima highway,and this model can effectively improve the accuracy of short-term traffic forecasts.

关 键 词：交通量预测 回归分析 GM模型 组合建模 

分 类 号：U494[交通运输工程—交通运输规划与管理]