The Forecast and the Optimization Control of the Complex Traffic Flow Based on the Hybrid Immune Intelligent Algorithm

摘要

Transportation system has time-varying, coupling and nonlinear dynamic characteristics. Traffic flow forecastis one of the key technologies of traffic guidance. It is very difficult to accurately forecast them effectively. This paper hasanalyzed the complexity and the evaluation index of urban transportation network and has proposed the forecasting modelof the hybrid algorithm based on chaos immune knowledge. First of all, the chaos knowledge is introduced into the topologystructure of immune network, so as to obtain the matching predictive values and knowledge base. Secondly, this algorithmcan dynamically control and adjusted the regional search speed and can fuse the information obtained by the chaosand immune algorithm, in order to realize the short-term traffic flow forecast. Finally, the simulation experiment showsthat the traffic flow forecasting error obtained by the method is small, feasible and effective and can better meet the needsof the traffic guidance system.