计算机科学 ›› 2010, Vol. 37 ›› Issue (2): 250-252.
• 人工智能 • 上一篇 下一篇
徐欣
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XU Xin
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摘要: 城市交通系统是一个非常复杂的非线性系统,很难建立精确的数学模型,而PP神经网络具有较强的自学习、自适应的特点,适合复杂的大系统。针对单交又路口红绿灯控制问题,基于改进的PP神经网络算法,同时考虑关键车流和非关键车流信息,提出并设计了两级加权神经网络控制器来进行实时控制。仿真结果表明,本方法优于传统控制方法。
关键词: 交通控制,神经网络,关键车流
Abstract: City traffic system is a very complicated non-linear system. It's very difficult to build precise mathematical model and BP neural network has advantage in self-study and self-adaption. In this paper, for the control problem in one intersection, based on improved BP neural network algorithm, considering key traffic flow and nonkcy traffic flow, hierarchical weighted neural network controller was proposed and desiged. It's used to control traffic on time. The simulation results show that this control method is better than traditional methods.
Key words: Traffic control,Neural network,Key traffic flow
徐欣. 城市单路口两级加权神经网络控制系统设计[J]. 计算机科学, 2010, 37(2): 250-252. https://doi.org/
XU Xin. Design of Hierarchical Weighted Neural Network Control System for City Traffic in Single Intersection[J]. Computer Science, 2010, 37(2): 250-252. https://doi.org/
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