Classifying, Clustering, and Grouping Demand Series
First Claim
1. A computer-program product tangibly embodied in a non-transitory machine-readable storage medium, the computer-program product including instructions configured to be executed to cause a data processing apparatus to:
- receive a plurality of time series included in a forecast hierarchy, each individual time series of the plurality of time series comprising one or more demand characteristics and a demand pattern for an item, the one or more demand characteristics including at least one of a demand lifecycle, an intermittence, or a seasonality, the demand pattern indicating one or more time intervals for which demand for the item is greater than a threshold value;
for each time series of the plurality of time series;
determine a classification for the individual time series based on the one or more demand characteristics;
determine a pattern group for the individual time series by comparing the demand pattern to demand patterns other time series in the plurality of time series; and
determine a level of the forecast hierarchy at which the each individual time series comprises an aggregate demand volume greater than a threshold amount;
generate an additional forecast hierarchy using the first forecast hierarchy, the classification, the pattern group, and the level, wherein utilizing the additional forecast hierarchy generates more accurate demand forecasts than demand forecasts generated utilizing the forecast hierarchy; and
provide, to a user of the computer-program product, forecast information related to at least one time series of the plurality of time series based on the additional forecast hierarchy.
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Accused Products
Abstract
Systems and methods for linear regression using safe screening techniques. A computing system may receive a plurality of time series included in a forecast hierarchy. For each time series, the computing system may determine a classification for the individual time series, a pattern group for the individual time series, and a level of the forecast hierarchy at which the each individual time series comprises an aggregate demand volume greater than a threshold amount. The computing system may generate an additional forecast hierarchy using the first forecast hierarchy, the classification, the pattern group, and the level. The computing system may provide, to the user of the system, forecast information related to at least one time series based on the additional forecast hierarchy.
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Citations
30 Claims
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1. A computer-program product tangibly embodied in a non-transitory machine-readable storage medium, the computer-program product including instructions configured to be executed to cause a data processing apparatus to:
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receive a plurality of time series included in a forecast hierarchy, each individual time series of the plurality of time series comprising one or more demand characteristics and a demand pattern for an item, the one or more demand characteristics including at least one of a demand lifecycle, an intermittence, or a seasonality, the demand pattern indicating one or more time intervals for which demand for the item is greater than a threshold value; for each time series of the plurality of time series; determine a classification for the individual time series based on the one or more demand characteristics; determine a pattern group for the individual time series by comparing the demand pattern to demand patterns other time series in the plurality of time series; and determine a level of the forecast hierarchy at which the each individual time series comprises an aggregate demand volume greater than a threshold amount; generate an additional forecast hierarchy using the first forecast hierarchy, the classification, the pattern group, and the level, wherein utilizing the additional forecast hierarchy generates more accurate demand forecasts than demand forecasts generated utilizing the forecast hierarchy; and provide, to a user of the computer-program product, forecast information related to at least one time series of the plurality of time series based on the additional forecast hierarchy. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9)
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10. (canceled)
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11. A computer-implemented method comprising:
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receiving a plurality of time series included in a forecast hierarchy, each individual time series of the plurality of time series comprising one or more demand characteristics and a demand pattern for an item, the one or more demand characteristics including at least one of a demand lifecycle, an intermittence, or a seasonality, the demand pattern indicating one or more time intervals for which demand for the item is greater than a threshold value; for each time series of the plurality of time series; determining, by a computing device, a classification for the individual time series based on the one or more demand characteristics; determining, by the computing device, a pattern group for the individual time series by comparing the demand pattern to demand patterns other time series in the plurality of time series; and determining, by the computing device, a level of the forecast hierarchy at which the each individual time series comprises an aggregate demand volume greater than a threshold amount; generating, by the computing device an additional forecast hierarchy using the first forecast hierarchy, the classification, the pattern group, and the level, wherein utilizing the additional forecast hierarchy generates more accurate demand forecasts than demand forecasts generated utilizing the first forecast hierarchy; and providing to a user of the computer-program product, forecast information related to at least one time series of the plurality of time series based on the additional forecast hierarchy.
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12-20. -20. (canceled)
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21. A system, comprising:
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a processor; and a non-transitory computer-readable storage medium including instructions configured to be executed that, when executed by the processor, cause the system to perform operations including; receiving a plurality of time series included in a forecast hierarchy, each individual time series of the plurality of time series comprising one or more demand characteristics and a demand pattern for an item, the one or more demand characteristics including at least one of a demand lifecycle, an intermittence, or a seasonality, the demand pattern indicating one or more time intervals for which demand for the item is greater than a threshold value; for each time series of the plurality of time series; determining a classification for the individual time series based on the one or more demand characteristics; determining a pattern group for the individual time series by comparing the demand pattern to demand patterns other time series in the plurality of time series; and determining a level of the forecast hierarchy at which the each individual time series comprises an aggregate demand volume greater than a threshold amount; generating an additional forecast hierarchy using the first forecast hierarchy, the classification, the pattern group, and the level, wherein utilizing the additional forecast hierarchy generates more accurate demand forecasts than demand forecasts generated utilizing the first forecast hierarchy; and providing to a user of the computer-program product, forecast information related to at least one time series of the plurality of time series based on the additional forecast hierarchy. - View Dependent Claims (22, 23, 24, 25, 26, 27, 28, 29, 30)
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Specification