Resources
Jump to Resources NavigationScientific Papers
Neural Computing in Product Formulation
Neural Computing in Product Formulation
R.C. Rowe and E.A. Colbourn*
Artificial intelligence techniques increasingly are being used to improve product formulations by developing models that relate alterations in ingredients and processing conditions to changes in observed properties. From relatively few applications in the early to mid-1990s, the use of neural computing in its broadest sense is gaining acceptance worldwide in a number of industry sectors. The new generation of formulators can expect to use these techniques routinely, making it timely for educators to be aware of his emerging new field. The paper outlines the key concepts underlying neural networks, fuzzy logic, genetic algorithms, and neurofuzzy systems, and reviews how these technologies have been used, singly and in combination, to model and optimize formulations in areas like pigments and dyes, adhesives, paints and coatings, and oils and lubricants.
Versions Available
- None
- Author: Prof. Ray Rowe
- Published Date: 01/07/03
- Journal: The Chemical Educator, 8, 211-218
Latest Scientific Papers
- A Major Advance in Crystal Structure Prediction
- Crystal structures of Quinacridones
- Crystal structure prediction of organic pigments: Quinacridone as an
- Asymmetric Crystal Growth of Resorcinol from the Vapor Phase: Surface Reconstruction and
- Concerted molecular displacements in a thermally-induced

