摘要
提出一种使用M atlab中的ANFIS模糊神经网络(FNN)工具箱来对传统的模糊控制器进行参数优化的方法,改善了控制器中的隶属度函数形状及分布,并应用于城市单交叉路口的多相位信号配时上.仿真实验证明所提出的算法可以降低车辆平均延误时间,保证车队更顺畅地通过交叉路口.
A parameter-optlmization algorithm is proposed to optimize parameters of traditional fuzzy controllers with ANFIS （adaptive neuro-fuzzy inference system）, a fuzzy neural network toolkit in Mafia.b. This algorithm improves the shape and distribution of membership functions of the controllers, and is applied to multi-phase traffic signal timing for the urban isolated intersection. All simulation results prove that the proposed algorithm can reduce average vehicle delay time and the vehicles can pass through intersections more smoothly.
出处
《信息与控制》
CSCD
北大核心
2006年第1期79-83,共5页
Information and Control
基金
辽宁省自然科学基金资助项目(20022032)
关键词
模糊神经网络
单交叉路口
信号配时
隶属度函数
fuzzy neural network （FNN）
isolated intersection
signal timing
membership function
