Base station traffic prediction method and system, storage medium and equipment

The invention relates to a base station traffic prediction method and system, a storage medium and equipment, and the method comprises the following steps: obtaining time sequence characteristics under different frequencies based on an original traffic time sequence in historical traffic data of a base station; taking the base stations as nodes, and constructing a node graph among the plurality of base stations by using the obtained time sequence characteristics; updating time sequence features by using a graph convolutional neural network based on the node graph, and generating node embedding; and establishing a time sequence relation for node embedding based on a time sequence convolutional network, constructing a prediction model of a base station flow sequence, and realizing base station flow prediction based on the constructed prediction model. The method can be used for traffic prediction of a plurality of mobile base stations, and an ideal prediction effect can be realized. 本发明涉及基站流量预测方法、系统、存储介质及设备，其中，