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FORECASTING AT LEAST ONE FEATURE TO BE FORECASTED

机译:预测至少一个要预测的功能

摘要

The invention is directed to a computer-implemented method for forecasting at least one feature to be forecasted; comprising the steps:a. Providing a train network (10), wherein the train network (10) represents a plurality of nodes (12) in a graph which are interconnected by respective edges (14); wherein each node (12) of the plurality of the nodes represents a train entity; wherein each edge (14) of the plurality of the edges represents a relationship between the train entities (S1); b. Providing an electrical grid (20), wherein the electrical grid (20) represents a plurality of nodes (22) in a graph which are interconnected by respective edges (24); wherein each node (22) of the plurality of the nodes represents an electrical entity; wherein each edge (24) of the plurality of the edges represents a relationship between the electrical entities (S2); c. Combining the train network (10) and the electrical grid (20) using a combined hybrid graph topology (30)(S3); d. Forecasting the respective at least one feature to be forecasted using a trained machine learning model based on the combined hybrid graph topology (30)(S4); and e. Providing the at least one forecasted feature (S5). Further, the invention relates to computing unit and a computer program product.
机译:本发明涉及一种用于预测要预测的至少一个特征的计算机实现的方法;包括步骤:a。提供列车网络(10),其中列车网络(10)表示在曲线图中的多个节点(12),其通过各个边缘(14)互连;其中多个节点的每个节点(12)表示列车实体;其中多个边缘的每个边缘(14)表示列车实体(S1)之间的关系;湾提供一种电网(20),其中电网(20)表示通过相应边缘(24)互连的曲线图中的多个节点(22);其中多个节点的每个节点(22)表示电实体;其中多个边缘的每个边缘(24)表示电实体(S2)之间的关系; C。使用组合的混合图拓扑(30)(S3)组合列车网络(10)和电网(20);天。根据组合的混合图拓扑(30)(S4)预测使用培训的机器学习模型预测要预测的相应至少一个功能;和e。提供至少一个预测特征(S5)。此外,本发明涉及计算单元和计算机程序产品。

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