Cooperative use of a genetic algorithm and an optimization trainer for autoencoder generation
US10733512B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | Dec 17, 2019 |
| Grant date | Aug 4, 2020 |
| Priority date | — |
| Expiry date | Dec 17, 2039 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N3/084
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A method includes, during an epoch of a genetic algorithm, determining a fitness value for each of a plurality of autoencoders. The fitness value for an autoencoder indicates reconstruction error responsive to data representing a first operational state of one or more devices. The method includes selecting, based on the fitness values, a subset of autoencoders. The method also includes performing a genetic operation with respect to at least one autoencoder to generate a trainable autoencoder. The method includes training the trainable autoencoder to reduce a loss function value to generate a trained autoencoder. The loss function value is based on reconstruction error of the trainable autoencoder responsive to data representative of a second operational state of the device(s). The method includes adding the trained autoencoder to a population to be provided as input to a subsequent epoch of the genetic algorithm.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.