Techniques for monitoring transformation techniques using control charts
First Claim
1. A forecasting system for applying forecasts and using outputs to implement remedial actions, comprising:
- a receiver that receives;
time series data including a plurality of current data points; and
a forecast model for a forecast applicable to the time series data;
a transformation engine that applies the forecast model to the time series data to produce a plurality of outputs;
a control engine that determines a set of control limits using a control chart and a set of residual values;
an anomaly detection engine that;
generates the set of residual values using the plurality of current data points and the plurality of outputs, wherein each residual value in the set of residual values indicates a difference between a current data point of the plurality of current data points and an output of the plurality of outputs; and
identifies one or more anomalies of the set of residual values based on the set of control limits and the control chart; and
a remedial-action engine that;
determines a remedial action list including a plurality of types of remedial actions;
assigns a prioritization to the types of remedial actions in the remedial action list, wherein prioritizations are based on computational costs of the remedial actions;
determines a remedial action for the forecast model based on the prioritizations of the types of remedial actions in the remedial action list and the one or more anomalies; and
perform the remedial action related to the forecast model.
1 Assignment
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Accused Products
Abstract
Techniques for applying transformation techniques and using transformation outputs to implement remedial actions are included. A system may include a receiver that may receive time series data including data points and one or more specifications for a transformation technique applicable to the time series data. The system may include a transformation engine that may apply the transformation technique to the time series data to produce outputs. The system may include a control engine that may determine a set of control limits using, for example, a control chart and a set of residual values. The system may include an anomaly detection engine that may generate the set of residual values using the current data points and the outputs. The anomaly detection engine may further identify one or more anomalies of the set of residual values based on the set of control limits and the control chart.
176 Citations
30 Claims
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1. A forecasting system for applying forecasts and using outputs to implement remedial actions, comprising:
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a receiver that receives; time series data including a plurality of current data points; and a forecast model for a forecast applicable to the time series data; a transformation engine that applies the forecast model to the time series data to produce a plurality of outputs; a control engine that determines a set of control limits using a control chart and a set of residual values; an anomaly detection engine that; generates the set of residual values using the plurality of current data points and the plurality of outputs, wherein each residual value in the set of residual values indicates a difference between a current data point of the plurality of current data points and an output of the plurality of outputs; and identifies one or more anomalies of the set of residual values based on the set of control limits and the control chart; and a remedial-action engine that; determines a remedial action list including a plurality of types of remedial actions; assigns a prioritization to the types of remedial actions in the remedial action list, wherein prioritizations are based on computational costs of the remedial actions; determines a remedial action for the forecast model based on the prioritizations of the types of remedial actions in the remedial action list and the one or more anomalies; and perform the remedial action related to the forecast model. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10)
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11. A non-transitory computer program product, tangible embodied in a non-transitory machine readable storage medium, including instructions operable to cause a data processing apparatus to:
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receive time series data including a plurality of current data points; receive a forecast model for a forecast applicable to the time series data; apply the forecast model to the time series data to produce a plurality of outputs; generate a set of residual values using the plurality of current data points and the plurality of outputs, wherein a residual value indicates a difference between a current data point of the plurality of data points and an output of the plurality of outputs; determine a set of control limits using a control chart and the set of residual values; identify one or more anomalies of the set of residual values, wherein anomalies are identified using the set of control limits and the control chart; determine a remedial action list including a plurality of types of remedial actions; assign a prioritization to the types of remedial actions in the remedial action list, wherein prioritizations are based on computational costs of the remedial actions; determine a remedial action for the forecast model based on the prioritizations of the types of remedial actions in the remedial action list and the one or more anomalies; and perform the remedial action related to the forecast model. - View Dependent Claims (12, 13, 14, 15, 16, 17, 18, 19, 20)
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21. A computer-implemented method for applying forecast models and using outputs to implement remedial actions, comprising:
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receiving time series data including a plurality of current data points; receiving a forecast model for a forecast applicable to the time series data; applying the forecast model to the time series data to produce a plurality of outputs; generating, using an anomaly detection engine, a set of residual values using the plurality of current data points and the plurality of outputs, wherein a residual value indicates a difference between a current data point of the plurality of data points and an output of the plurality of outputs; determining a set of control limits using a control chart and the set of residual values; identifying, using the anomaly detection engine, one or more anomalies of the set of residual values, wherein anomalies are identified using the set of control limits and the control chart; determining, using a remedial-action engine, a remedial action list including a plurality of types of remedial actions; assigning, using the remedial-action engine, a prioritization to the types of remedial actions in the remedial action list, wherein prioritizations are based on computational costs of the remedial actions; determining, using the remedial-action engine, a remedial action for the forecast model based on the prioritizations of the types of remedial actions in the remedial action list and the one or more anomalies; and performing, using the remedial-action engine, the remedial action related to the forecast model. - View Dependent Claims (22, 23, 24, 25, 26, 27, 28, 29, 30)
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Specification