摘要
交通拥堵日益显著,已对城市的经济、环境和社会发展造成不良影响,神经网络算法作为先进的机器学习技术,已经广泛应用于交通拥堵预测领域。文章综述神经网络算法在交通拥堵预测中的应用,包括交通拥堵预测算法的发展、神经网络算法的原理和应用现状,以及未来发展方向。
Traffic congestion is becoming increasingly significant and has had a negative impact on the economy,environment,and social development of cities.As an advanced machine learning technology,neural network algorithms have been widely applied in the field of traffic congestion prediction.This article will provide an overview of the application of neural network algorithms in traffic congestion prediction,including the development of traffic congestion prediction algorithms,the principles and application status of neural network algorithms,and future development directions.
作者
张金芳
李亚娟
戎静怡
贾冬青
裴祥喜
ZHANG Jinfang;LI Yajuan;RONG Jingyi;JIA Dongqing;PEI Xiangxi(Computer Department,Hebei University of Water Resources and Electric Engineering,Cangzhou Hebei 061016,China;Personnel Division,Hebei University of Water Resources and Electric Engineering,Cangzhou Hebei 061016,China)
出处
《信息与电脑》
2023年第19期4-6,共3页
Information & Computer
基金
河北省教育厅科学研究项目资助“基于大数据技术的时滞传染病预测模型研究”(项目编号:ZC2021237)。
关键词
交通流
神经网络
拥堵预测
图神经网络
traffic flow
neural network
congestion prediction
graph neural network
