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The Study of Traffic Flow Information Completion Based on GAN Algorithm

机译:基于GAN算法的交通流信息补全研究。

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In urban road traffic, detectors often cause incomplete data and missing data as a result of inadequate coverage or equipment damage and other reasons. Therefore, the data needs to be repaired to ensure data support for the traffic management service. This paper regards traffic flow data from section geomagnetic detectors as the object, processing graphically section flow information. And the missing data of network is predicted and complemented by the idea of generating network analysis images. This paper analyzes the influence of missing area size and loss at random of data on the accuracy of complete information. The results prove the feasibility and applicability of this method.
机译:在城市道路交通中,由于覆盖范围不足或设备损坏以及其他原因,检测器通常会导致数据不完整和数据丢失。因此,需要修复数据以确保对流量管理服务的数据支持。本文将来自地磁探测器的交通流量数据作为对象,以图形方式处理截面流量信息。并通过生成网络分析图像的思想来预测和补充网络的丢失数据。本文分析了数据丢失区域的大小和随机丢失对完整信息准确性的影响。结果证明了该方法的可行性和适用性。

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