| DCW算法在智能交通系统中的应用研究 |
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| 引用本文： | 朱坤,李文杰.DCW算法在智能交通系统中的应用研究[J].天津理工大学学报,2010,26(1):17-20. |
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| 作者姓名： | 朱坤 李文杰 |
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| 作者单位： | 天津理工大学,计算机与通信工程学院,天津,300384 |
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| 基金项目： | 国家自然科学基金，软件新技术重点实验室和计算机视觉与系统省部共建教育部共建教育部重点实验室资助 |
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| 摘 要： | 针对城市交通路网具有实时性的特点,为了快速高效地选择出最优路径,采用一种动态改变惯性的自适应粒子群算法(DCW).在DCW算法中引入参数粒子群简化速度因子和聚集度因子,在每次迭代时算法根据当前粒子群进化速度和聚集度动态改变惯性权值.最后用惯性权值线性递减粒子群算法(LDW)和DCW算法分别进行计算最优路径的仿真实验,得出结论,DCW算法更适合用作智能交通系统中最优路径的选择.
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| 关 键 词： | 最优路径 动态改变惯性的自适应粒子群算法（DCW） 惯性权值线性递减粒子群算法（LDW） 智能交通系统 |
DCW-PSO algorithm and its application in intelligent transportation systems |
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| ZHU Kun,LI Wen-jie.DCW-PSO algorithm and its application in intelligent transportation systems[J].Journal of Tianjin University of Technology,2010,26(1):17-20. |
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| Authors: | ZHU Kun LI Wen-jie |
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| Institution: | ZHU Kun,LI Wen-jie(School of Computer , Communications Engineering,Tianjin University of Technology,Tianjin 300384,China) |
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| Abstract: | Based on the urban traffic network's real-time characteristic,a particle swarm optimization with dynamically changing weight(DCW-PSO) is adopted in order to search the optimal path quickly and efficiently.This algorithm brings in the factors of evolution speed and aggregation degree,based on which the weight is changed dynamically in each iteration process.Finally,the DCW-PSO proposed in this paper and the algorithm of particle swarm optimization with linearly decreasing weight(LDW-PSO) are tested separatel... |
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| Keywords: | optimal path particle swarm optimization with dynamically changing weight(DCW-PSO) particle swarm optimization with linearly decreasing weight(LDW-PSO) intelligent transportation systems |
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