Method and apparatus for determining the sensitivity of inputs to a neural network on output parameters
US5825646A · kind A · utility
Assignee
Inventors
Key dates
| Filing date | Jun 3, 1996 |
| Grant date | Oct 20, 1998 |
| Priority date | — |
| Expiry date | Jun 3, 2016 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N3/09
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A distributed control system (14) receives on the input thereof the control inputs and then outputs control signals to a plant (10) for the operation thereof. The measured variables of the plant and the control inputs are input to a predictive model (34) that operates in conjunction with an inverse model (36) to generate predicted control inputs. The predicted control inputs are processed through a filter (46) to apply hard constraints and sensitivity modifiers, the values of which are received from a control parameter block (22). During operation, the sensitivity of output variables on various input variables is determined. This information can be displayed and then the user allowed to select which of the input variables constitute the most sensitive input variables. These can then be utilized with a control network (470) to modify the predicted values of the input variables. Additionally, a neural network (406) can be trained on only the selected input variables that are determined to be the most sensitive. In this operation, the network is first configured and trained with all input nodes and with all training data. This provides a learned representation of the output wherein th…
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.