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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.

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  • Author: Prof. Ray Rowe
  • Published Date: 01/07/03
  • Journal: The Chemical Educator, 8, 211-218

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