Empirical design of experiments using neural network models
US7451122B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Mar 29, 2006 |
| Grant date | Nov 11, 2008 |
| Priority date | — |
| Expiry date | Jan 3, 2027 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N3/02
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Methods and apparatus are provided pertaining to a design of experiments. The method comprises generating a data set from historical data; identifying and removing any fault data points in the data set so as to create a revised data set; supplying the data points from the revised data set into a nonlinear neural network model; and deriving a simulator model characterizing a relationship between the input variables and the output variables. The apparatus comprises means for generating a data set from historical data; means for identifying and removing any fault data points in the data set so as to create a revised data set; means for supplying the data points from the revised data set into a nonlinear neural network model; and means for deriving a simulator model characterizing a relationship between the input variables and the output variables.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.