城市交通流量智能组合预测方法研究

智能交通系统是目前世界上公认的解决城市交通拥堵问题的最佳措施，实时、准确的交通流量预测是智能交通系统实现的关键技术之一，也是实现智能交通诱导及控制的前提。文章对几种重要的交通流量预测模型的理论和优缺点进行了比较，分析了影响预测模型的因素，提出了一种智能组合预测方法。该方法利用遗传算法群体搜索的特点，组合各种算法，优化预测思路，充分发掘不同算法的差异优势，实践证明该思路是切实可行的。

Research of Combined Prediction for City Traffic Flow Based on Genetic Algorithm

The intelligent Transportation System is the best measure for the solution of the urban traffic jam in the world,and forecasting urban traffic network is the premise for developing urban intelligent transportation system.In this paper,some important forecasting models,including the theory and characteristic,are discussed,and the factors influencing the forecasting model are discussed.In the end,the combined prediction of city traffic flow based on genetic algorithm is given using the characteristics of genetic algorithm's colony search. The new algorithm combines all kinds of algorithms,optimizes the prediction schemes,fully discovers the advantages of different algorithms,and is proved to be practical and productive.