Dual stage attention based recurrent neural network for time series prediction
US10929674B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Aug 28, 2017 |
| Grant date | Feb 23, 2021 |
| Priority date | — |
| Expiry date | Dec 22, 2039 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06V20/44
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Systems and methods for time series prediction are described. The systems and methods include encoding driving series into encoded hidden states, the encoding including adaptively prioritizing driving series at each timestamp using input attention, the driving series including data sequences collected from sensors. The systems and methods further includes decoding the encoded hidden states to generate a predicting model, the decoding including adaptively prioritizing encoded hidden states using temporal attention. The systems and methods further include generating predictions of future events using the predicting model based on the data sequences. The systems and methods further include generating signals for initiating an action to devices based on the predictions.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.