The invention discloses a multi-node traffic flow prediction method based on a simplified attention mechanism, and belongs to the field of traffic flow prediction, and the method comprises the steps: employing a multi-node traffic flow prediction model, and predicting the traffic flow data of a node in a future T time period according to the traffic flow data of a node in a previous T time period; the multi-node traffic flow prediction model comprises a data embedding layer, a simplified attention layer and an output layer; the simplified attention layer comprises a heterogeneous attention separation layer, a simplified attention module and a heterogeneous attention aggregation layer; the simplified attention module comprises a TSA module, an SSA module and a GSA module; according to the method, the calculation speed of the attention can be increased by adopting a simplified attention mechanism, and the SSA module and the GSA module can better extract the geographical similarity dependence between the nodes and the similarity dependence on the change mode; therefore, the accuracy of model prediction is effectively improved.
本发明公开了一种基于简化注意力机制的多节点交通流量预测方法,属于交通流量预测领域,该方法包括:采用多节点交通流量预测模型,以上一个T时段的节点交通流量数据,预测未来T时段节点的交通流量数据;所述多节点交通流量预测模型包括数据嵌入层、简化注意力层和输出层;所述简化注意力层,包括异构注意力分离层、简化注意力模块和异构注意力聚合层;所述简化注意力模块包括TSA模块、SSA模块和GSA模块;本发明采用了简化注意力机制可以加快注意力的计算速度,其中SSA模块、GSA模块可以更好的提取节点之间地理上的相似性依赖,以及变化模式上的相似性依赖;从而有效地提高模型预测的精准度。
Multi-node traffic flow prediction method based on simplified attention mechanism
一种基于简化注意力机制的多节点交通流量预测方法
24.01.2025
Patent
Elektronische Ressource
Chinesisch
IPC: | G08G Anlagen zur Steuerung, Regelung oder Überwachung des Verkehrs , TRAFFIC CONTROL SYSTEMS |
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