单片机与嵌入式系统应用2019，Vol.19Issue(3)：72-75,4.
基于深度学习的LSTM的交通流量预测
Traffic Flow Prediction Based on Deep Learning LSTM Network
庞悦 1赵威 1张雅楠 1许宏科1
作者信息
- 1. 长安大学 电子与控制工程学院, 西安 710064
- 折叠
摘要
Abstract
Traffic flow prediction is one of the key basic technologies of intelligent transportation system, which directly affects the realization of traffic control and induction system.In view of existing prediction methods can not fully reveal the essence of traffic flow, this paper proposes a forecasting model based on depth learning.The traffic flow is predicted by using long short-term memory network.The experiment results show that the proposed prediction model has high accuracy and is an effective method for traffic flow prediction.关键词
深度学习/LSTM/交通流预测Key words
deep learning/LSTM/traffic flow prediction分类
交通工程引用本文复制引用
庞悦,赵威,张雅楠,许宏科..基于深度学习的LSTM的交通流量预测[J].单片机与嵌入式系统应用,2019,19(3):72-75,4.
