Systems and methods for forecasting time series with variable seasonality
US11138090B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Oct 23, 2018 |
| Grant date | Oct 5, 2021 |
| Priority date | — |
| Expiry date | Feb 29, 2040 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06F2201/835
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Techniques for training and evaluating seasonal forecasting models are disclosed. In some embodiments, a network service generates, in memory, a set of data structures that separate sample values by season type and season space. The set of data structures may include a first set of clusters corresponding to different season types in the first season space and a second set of clusters corresponding to different season types in the second season space. The network service merges two or more clusters the first set and/or second set of clusters. Clusters from the first set are not merged with clusters from the second set. After merging the clusters, the network service determines a trend pattern for each of the remaining clusters in the first and second set of clusters. The network service then generates a forecast for a metric of a computing resource based on the trend patterns for each remaining cluster.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.