| 基于主从粒子群的模糊小波神经网络交通控制 |
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| 引用本文： | 于万霞,杜太行.基于主从粒子群的模糊小波神经网络交通控制[J].计算机仿真,2009,26(4). |
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| 作者姓名： | 于万霞 杜太行 |
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| 作者单位： | 1. 天津工程师范学院电子工程系,天津,300222;河北工业大学,天津,300130
2. 河北工业大学,天津,300130 |
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| 摘 要： | 城市交通智能控制是ITS的重要组成部分,交叉口是决定道路通行顺畅的制的基础.为提高路口的通行能力,提出了主从结构的粒子群算法优化模糊小波神经网络参数,并将其应用于交通信号的控制.算法中,主级粒子进行全局搜索,从级粒子以主级粒子找到的最优解为中心进行局部搜索.仿真结果表明该算法能够有效减少交叉口车辆平均延误时间,提高道路通行能力.
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| 关 键 词： | 交通控制 模糊小波神经网络 车辆平均延误 粒子群算法 |
A Fuzzy Wavelet Neural Network Traffic Control method Based on Master-slave PSO |
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| YU Wan-xia,DU Tai-hang.A Fuzzy Wavelet Neural Network Traffic Control method Based on Master-slave PSO[J].Computer Simulation,2009,26(4). |
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| Authors: | YU Wan-xia DU Tai-hang |
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| Affiliation: | 1.Department of Electronics Technology;Tianjin Univ.of Technology and Education;Tianjin 300222;China;2.Hebei Univ.of Tech.;Tianjin 300130;China |
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| Abstract: | In modern times,the intelligent control of urban traffic is an important part of ITS.The intersection acts as the key factor in deciding the road traffic.The traffic control system is based on real time control of isolated intersection.To solve traffic signal control,a hierarchical structure particle swarm optimization(PSO) algorithm is proposed to train the fuzzy wavelet neural network..In the algorithm,the global search is performed at the master level,while the local search is carried out at the slave le... |
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| Keywords: | Traffic control Fuzzy wavelet neural network Average vehicle delay Particle swarm optimization algorithm |
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