The invention discloses a traffic flow prediction method based on an IGA-Bi-LSTM, and the method comprises the steps: collecting traffic flow data, carrying out the data abnormality, data missing and data filling processing operation, and obtaining complete traffic flow data after the data updating is completed; for a predicted road section, dividing complete traffic flow data and traffic flow data of adjacent lanes into a training set and a test set according to a set proportion, and generating spatial-temporal correlation by adopting a sliding window to serve as input data of a prediction model; an IGA-Bi-LSTM short-term traffic flow prediction model is established; based on the optimizer Adam, the training set data is adopted to carry out iterative training on the IGA-Bi-LSTM short-term traffic flow prediction model; and adopting the trained IGA-Bi-LSTM short-term traffic flow prediction model to carry out short-term traffic flow prediction on the test set, adopting the performance index to carry out evaluation, and outputting a prediction model meeting the performance index. The method can effectively solve the problems of poor traffic flow prediction precision and slow efficiency in the prior art, and has a better effect on traffic flow prediction.
本发明公开了一种基于IGA‑Bi‑LSTM的交通流预测方法,包括:采集交通流数据,并对其进行数据异常、数据缺失、数据填充处理操作,完成数据更新后,得到完整交通流数据;对预测路段,将完整交通流数据和相邻车道的交通流数据,按照设定的比例划分为训练集和测试集,采用滑动窗口生成时空相关性,作为预测模型的输入数据;建立IGA‑Bi‑LSTM短时交通流预测模型;基于优化器Adam,采用训练集数据对IGA‑Bi‑LSTM短时交通流预测模型进行迭代训练;采用训练好的IGA‑Bi‑LSTM短时交通流预测模型对测试集进行短时交通流预测,采用性能指标进行评估,输出满足性能指标的预测模型。本发明能有效解决现有技术针对现有交通流预测精度较差、效率较慢的问题,对交通流预测具有更好的效果。
Traffic flow prediction method based on IGA-Bi-LSTM
一种基于IGA-Bi-LSTM的交通流预测方法
2025-02-18
Patent
Electronic Resource
Chinese
IPC: | G08G Anlagen zur Steuerung, Regelung oder Überwachung des Verkehrs , TRAFFIC CONTROL SYSTEMS |
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