Predicting traffic flow changes by fuzzy logic

摘要：

Fuzzy models with hybrid algorithms of adaptation allow to predict complex temporary processes successfully. This article shows how we can use fuzzy difference TSK model for traffic flow predictions. Described hybrid algorithm, it uses fuzzy logic, neuro - fuzzy network and recurrent algorithm. Hybrid algorithm consists of two types identifications: parametric and structural. We apply it for traffic data from California and compare with another prediction methods.

关键词： system model fuzzy model the rule of inference parameter estimation hybrid algorithm traffic flow.

作者: Kamenev A.V. Pashchenko F.F. Kudinov Y.I.

作者单位: Institute of Control Sciences V.A. Trapeznikov, Russian Academy of Sciences, Moscow 117997 Lipetsk State Technical University, Lipetsk 398600

会议类型: 国际会议

会议名称: The 24th Chinese Control and Decision Conference (第24届中国控制与决策学术年会 2012 CCDC)

会议地点: 太原

会议语种:英文

页码: 1582-1584

在线出版日期: 2012-05-23（万方平台首次上网日期，不代表论文的发表时间）