基于前馈神经网络算法的高速公路交通态势信息化识别方法  

Information Recognition Method for Highway Traffic Situation Based on Feedforward Neural Network Algorithm

作　　者：万万 刘荣 谭军 WAN Wan;LIU Rong;TAN Jun(China Railway Construction Kunlun Investment Group Co.,Ltd.,Chengdu 610000,China;Chengdu JinSui Automation Engineering Co.,Ltd.,Chengdu 610000,China)

机构地区：[1]中国铁建昆仑投资集团有限公司,四川成都610000 [2]成都金隧自动化工程有限责任公司,四川成都610000

出　　处：《微型电脑应用》2025年第1期197-200,共4页Microcomputer Applications

摘　　要：为了精准识别高速公路交通态势,保障车辆的安全畅通,研究基于前馈神经网络算法的高速公路交通态势信息化识别方法。通过模糊聚类算法划分高速公路交通态势数据的类别;构建基于前馈神经网络的信息化识别模型,输出高速公路交通态势识别结果。测试结果表明,所提方法识别结果的MAE区间为[5.12,6.96],MAPE区间为[9.88%,11.52%],识别精度较高,可以保障车辆的安全通行。In order to accurately identify the expressway traffic situation and ensure the safety and smoothness of vehicles,an expressway traffic situation information recognition method based on feedforward neural network algorithm is studied.The data of expressway traffic situation are classified by fuzzy clustering algorithm,and the information recognition model based on feedforward neural network is constructed to output the results of expressway traffic situation recognition.The test results show that the MAE range of the recognition results of the proposed method is 5.12~6.96,and the MAPE range is 9.88%~11.52%.The recognition accuracy is higher,which can ensure the safe passage of vehicles.

关 键 词：前馈神经网络 高速公路 交通态势 信息化识别 模糊聚类算法 交通流参数 

分 类 号：U491[交通运输工程—交通运输规划与管理]