Using a machine learning module to perform preemptive identification and reduction of risk of failure in computational systems
US11200103B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Oct 26, 2018 |
| Grant date | Dec 14, 2021 |
| Priority date | — |
| Expiry date | Jan 22, 2039 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N5/046
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Input on a plurality of attributes of a computing environment is provided to a machine learning module to produce an output value that comprises a risk score that indicates a likelihood of a potential malfunctioning occurring within the computing environment. A determination is made as to whether the risk score exceeds a predetermined threshold. In response to determining that the risk score exceeds a predetermined threshold, an indication is transmitted to indicate that potential malfunctioning is likely to occur within the computing environment. A modification is made to the computing environment to prevent the potential malfunctioning from occurring.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.