Adaptive selection of machine learning/deep learning model with optimal hyper-parameters for anomaly detection of connected equipment
US12032344B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jul 6, 2023 |
| Grant date | Jul 9, 2024 |
| Priority date | — |
| Expiry date | Jul 6, 2043 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N7/01
- WIPO fieldControl
- WIPO sectorInstruments
Abstract
A model management system for building equipment includes one or more memory devices configured to store instructions that, when executed on one or more processors, cause the one or more processors to determine whether fault data exists in equipment data used to generate a plurality of shutdown prediction models for the building equipment, generate a first performance evaluation value for each of the plurality of shutdown prediction models using a first evaluation technique in response to a determination that the fault data exists in the equipment data, generate a second performance evaluation value for each of the plurality of shutdown prediction models using a second evaluation technique in response to a determination that the fault data does not exist in the equipment data, and select one of the plurality of shutdown prediction models based on the first performance evaluation value and the second performance evaluation value.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.