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 forecast is one of the key technologies traffic guidance. It very difficult to accurately them effectively. This paper analyzed complexity evaluation index urban transportation network proposed forecasting model hybrid algorithm based on chaos immune knowledge. First all, knowledge introduced into topol- ogy structure network, so as obtain matching predictive values base. Secondly, this algo- rithm can dynamically control adjusted regional search speed fuse information obtained by algorithm, in order realize short-term forecast. Finally, simulation experiment shows that error method small, feasible effective better meet needs guidance system.