CAJ | 학술논문

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。
위료해결일익복잡다변적성시교통상황，개선성시교통계통，본문장지능교통계통여신경망락방법상결합，대취약적성시교통계통진행우화。수선토론료지능교통계통적현상급개진조시，접착토론료기우신경망락대교통류진행예측，최후진일보기우신경망락대교통계통적중요삼수——록신비진행설계。본문장인진지능교통계통병종합채용신경망락대현유교통계통적연구，대목전취약적성시교통계통진행설계여우화。
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.