| CPC G06Q 10/0635 (2013.01) [G06F 17/15 (2013.01); G06F 18/2433 (2023.01); G06N 20/00 (2019.01); G06Q 10/04 (2013.01); G06Q 10/067 (2013.01)] | 20 Claims |
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1. A computing system comprising:
a hardware processor configured to:
receive, by a machine learning model including a time-series forecasting model, first time-series signal captured of a first data value, a second time-series signal captured of a second data value, and a third time-series signal captured of a third data value,
detect, by an anomaly detector, a causal relationship between a recurring anomaly in the first time-series signal and co-occurring anomalies in the second and third time series signals based on a delay in time between the recurring anomaly in the first time-series signals and the co-occurring anomalies in the second and third time-series signals,
build, by a causal graph builder, a graph model comprising a first node representing the first time-series signal, a second node representing the second time-series signal, a third node representing the third time-series signal, an operator node between the first, second, and third nodes, and edges between the nodes identifying the causal relationship, and store the graph model in a graph data store,
receive, by the machine learning model including the time-series forecasting model, a new time-series signal of the second data value and a new time-series signal of the third data value,
predict, by the machine learning model including the time-series forecasting model, that a future anomaly will occur within a future time-series signal of the first data value based on a new occurrence of the co-occurring anomalies in the new time-series signals of the second and third data values and the first node, second node, third node, operator node, and edges in the graph model;
display a graph of the future time-series signal of the first data value along a time axis within a user interface and display an indicator of the future anomaly at a future point in time on the graph of the time-series signal of the first data value corresponding to when the future anomaly will occur and a textual explanation, generated by an anomaly alerter, of the basis of the future anomaly including information regarding the co-occurring anomalies in the new time-series signals of the second and third data values; and
transmit an alert of the predicted future anomaly, prior to an occurrence of the future anomaly, to a connected system to perform at least one of an action to prevent the anomaly and an action to make an adjustment prior to the occurrence of the predicted future anomaly.
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