The invention provides a short-time traffic flow prediction method and system, a storage medium, equipment and a terminal, and the method comprises the following steps: S1, collecting short-time traffic flow data, and constructing a traffic flow input matrix according to the short-time traffic flow data; s2, performing feature extraction on the traffic flow input matrix by using a convolutional neural network to obtain spatial features of adjacent monitoring points; s3, performing time feature extraction on the spatial features based on a long-short-term memory network to obtain the time features, and constructing a convolutional long-short-term memory network model; s4, optimizing the convolutional long-short term memory network model by using an attention mechanism, and extracting periodic features of the traffic flow data; and S5, carrying out deep fusion on the spatial features, the time features and the periodic features to obtain the flow data of all the monitoring points at the next moment. According to the method, the spatial dimension of the traffic flow input matrix is processed, so that the capturing capability of spatial correlation is enhanced.
本发明提出了一种短时交通流量预测方法、系统、存储介质、设备及终端,方法包括以下步骤:S1、采集短时交通流量数据,根据所述短时交通流量数据构建交通流量输入矩阵;S2、使用卷积神经网络对交通流量输入矩阵进行特征提取,获取相邻监测点的空间特征;S3、所述空间特征基于长短时记忆网络对进行时间特征提取,得到时间特征并构建卷积长短时记忆网络模型;S4、使用注意力机制优化卷积长短时记忆网络模型,并提取交通流数据的周期特征;S5、将空间特征、时间特征与周期特征进行深层次融合,得到所有监测点在下一时刻的流量数据。本申请通过对交通流量输入矩阵的空间维度进行处理,增强了对空间相关性的捕捉能力。
Short-term traffic flow prediction method and system, storage medium, equipment and terminal
短时交通流量预测方法、系统、存储介质、设备及终端
2024-02-27
Patent
Electronic Resource
Chinese
IPC: | G08G Anlagen zur Steuerung, Regelung oder Überwachung des Verkehrs , TRAFFIC CONTROL SYSTEMS / G06F ELECTRIC DIGITAL DATA PROCESSING , Elektrische digitale Datenverarbeitung / G06N COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS , Rechnersysteme, basierend auf spezifischen Rechenmodellen |
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