The invention discloses an algorithm model for complementing traffic data acquisition missing of a traffic operation system. The algorithm model comprises the following steps: determining a traffic data missing road section and a traffic data missing time period; acquiring traffic data of a traffic data missing road section and nearby road sections; extracting spatial correlation; and complementing the missing traffic data of the missing road section according to the spatial correlation. According to the method, the spatial correlation characteristics between the traffic data of the current road section and the traffic data of the nearby road sections are extracted through the deep learning model, the traffic data are complemented according to the spatial correlation characteristics, and the method has the advantages that long-time missing of the traffic data can be complemented, and the complementing effect is good.
本发明公开了一种交通运行体系流量数据采集缺失补全的算法模型,包括如下步骤:确定交通数据缺失路段和时间段;获取交通数据缺失路段及其附近路段的交通数据;提取空间相关性;根据空间相关性补全缺失路段缺失的交通数据。本发明叙述的方法通过深度学习模型提取当前路段与附近路段的交通数据之间的空间相关特征,并根据空间相关特性进行交通数据补全,具有能对长时间的交通数据的缺失进行补全,补全效果好的优点。
Algorithm model for complementing flow data acquisition missing of traffic operation system
交通运行体系流量数据采集缺失补全的算法模型
2022-03-08
Patent
Electronic Resource
Chinese
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