Systems and methods for an accelerating product formulation creation via implementing a machine learning-derived graphical formulation network model
US11783103B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Feb 2, 2023 |
| Grant date | Oct 10, 2023 |
| Priority date | — |
| Expiry date | Feb 2, 2043 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06F2111/08
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A method and system for implementing one or more machine learning models for accelerating formulation design for a target product that includes converting an unsupervised formulation network model to a supervised formulation network model, deriving an outcome-contributory value for each of a plurality of distinct design variables of the supervised formulation network, identifying a dependency connection between each of a plurality of distinct pairs of distinct design variables, computing a strength of connection metric value for each of the plurality of distinct pairs of distinct design variables; and generating, via a graphical user interface, a graphical rendering of the supervised formulation model that may be manipulated to accelerate for design of a proposed formulation for a target physical product.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.