Execution of a genetic algorithm with variable evolutionary weights of topological parameters for neural network generation and training
US11106978B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Sep 8, 2017 |
| Grant date | Aug 31, 2021 |
| Priority date | — |
| Expiry date | Jul 2, 2040 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N20/10
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A method includes generating, by a processor of a computing device, an output set of models corresponding to a first epoch of a genetic algorithm and based on an input set of models of the first epoch. The input set and the output set includes data representative of a neural network. The method includes determining a particular model of the output set based on a fitness function. A first topological parameter of a first model of the input set is modified to generate the particular model of the output set. The method includes modifying a probability that the first topological parameter is to be changed by a genetic operation during a second epoch of the genetic algorithm that is subsequent to the first epoch. The method includes generating a second output set of models corresponding to the second epoch and based on the output set and the modified probability.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.