Reduction of fitness evaluations using clustering techniques and neural network ensembles
US7363281B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jan 24, 2005 |
| Grant date | Apr 22, 2008 |
| Priority date | — |
| Expiry date | May 17, 2025 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N3/126
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
The invention relates to an evolutionary optimization method. First, an initial population of individuals is set up and an original fitness function is applied. Then the offspring individuals having a high evaluated quality value as parents are selected. In a third step, the parents are reproduced to create a plurality of offspring individuals. The quality of the offspring individuals is evaluated selectively using an original fitness function or an approximate fitness function. Finally, the method returns to the selection step until a termination condition is met. The step of evaluating the quality of the offspring individuals includes grouping all offspring individuals in clusters, selecting for each cluster one or a plurality of offspring individuals, resulting in altogether selected offspring individuals, evaluating the selected offspring individuals by the original fitness function, and evaluating the remaining offspring individuals by means of the approximate fitness function.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.