摘要
为了解决日益复杂多变的城市交通状况,改善城市交通系统,本文将智能交通系统与神经网络方法相结合,对脆弱的城市交通系统进行优化。首先讨论了智能交通系统的现状及改进措施,接着讨论了基于神经网络对交通流进行预测,最后进一步基于神经网络对交通系统的重要参数——绿信比进行设计。本文将引进智能交通系统并综合采用神经网络对现有交通系统的研究,对目前脆弱的城市交通系统进行设计与优化。
In order to solve the increasingly complex urban trafifc conditions and improve the urban transportation system, this paper combines the intelligent trafifc system with neural network methods and optimizes the vulnerable urban traffic systems. Firstly, this paper discusses the status of intelligent transportation systems and improvement measures. Secondly, it discusses the prediction of traffic flow based on neural network. Last but not least, based on neural network, it further designs the green ratio which is the important parameter of trafifc system. This paper introduces the intelligent trafifc system and the study of existing trafifc system with the combination of neural network to design and optimize the current fragile urban transport system.
出处
《新型工业化》
2015年第4期18-23,共6页
The Journal of New Industrialization
基金
国家自然科学基金面上项目(61174116)资助
2014年北京市大学生科学研究与创业行动计划项目资助
北京市自然科学基金资助项目(4154068
4142014)
关键词
智能交通系统
神经网络
交通流
绿信比
优化
intelligent traffic system
neural network
traffic flow
green ratio
optimization
