基于知识免疫计算的交通流量预测方法研究

Research on Traffic Flow Forecasts Method Based on Knowledge Immune Optimization

随着交通行业的快速发展,交通事故,道路拥堵和交通堵塞日益严重影响我们的日常生活。为了提高道路的使用效率,引入知识免疫的新思路,目的是在智能交通网下解决交通流量的预测问题。在数学模型的基础上,设计并提出一种基于知识免疫车辆预测方案,并在仿真环境中进行实验。结果表明,该算法能收敛多目标优化问题并提供合理的交通流量导向方案,为交通流量预测模式提供方向,具有良好的价值。

With the rapid development of the transport industry, traffic accidents, road congestion and traffic congestion are becoming more frequent serious affected on us. For improving the efficiency, introduces the new ideas knowledge immunity to solve the traffic prediction problem in the intelligent transportation network. Gives a VRP program based on knowledge of the immune optimization, designs a mathematical model, conductes experiments in the simulation environment. The results show that the algorithm can make the multi-objective opti- mization problem converge to the optimal solution set, be able to provide reasonable flow guide scheme, provides the direction model for traffic flow prediction, has good application value.