The invention discloses a traffic flow short-term prediction optimization application method based on a time convolution network. The method comprises the following steps: collecting traffic flow data information; preprocessing the data information, and counting the actual value of the traffic flow; constructing a time convolutional network according to the actual value, and training the network; and inputting real-time data of the traffic flow into the trained time convolutional network to realize short-term prediction of the traffic flow. According to the method, when the time convolution network is used for processing the prediction problem, the defect of capability of utilizing historical data with long time span or high spatial similarity is overcome, and the precision of short-term traffic flow prediction is improved.
本发明公开了一种基于时间卷积网络的车流量短期预测优化应用方法,包括采集车流量数据信息;对所述数据信息进行预处理,统计车流量的实际值;根据所述实际值构建时间卷积网络,并对所述网络进行训练;将车流量的实时数据输入训练好的所述时间卷积网络,实现对车流量的短期预测。本发明方法在利用时间卷积网络在处理预测问题时,解决了利用时间跨度长或空间相似度高的历史数据能力的缺陷,提高了短期车流量预测的精度。
Traffic flow short-term prediction optimization application method based on time convolution network
一种基于时间卷积网络的车流量短期预测优化应用方法
2021-07-27
Patent
Electronic Resource
Chinese
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