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A knowledge-based pattern recognition approach for the prediction of bubble size distribution in Newtonian fluids at high pressure
- Source :
- Chemical Engineering Journal. 112:131-135
- Publication Year :
- 2005
- Publisher :
- Elsevier BV, 2005.
-
Abstract
- The knowledge-based pattern recognition (KE) approach provides a basis for classification of state of fluid systems. The new method determines bubble size distribution at high pressure that is very important for the brewery industry and other alcoholic beverages (champagne). Conforming to the principle of “decreasing precision with increasing intelligence”, the KE approach has been applied to the determination of bubble size distribution. An important feature of these architectures is that they do not require global mathematical modeling of the system.
- Subjects :
- Basis (linear algebra)
business.industry
Computer science
General Chemical Engineering
Bubble
Pattern recognition
General Chemistry
Fuzzy logic
Industrial and Manufacturing Engineering
Distribution (mathematics)
Pattern recognition (psychology)
Particle-size distribution
Newtonian fluid
Feature (machine learning)
Environmental Chemistry
Artificial intelligence
business
Subjects
Details
- ISSN :
- 13858947
- Volume :
- 112
- Database :
- OpenAIRE
- Journal :
- Chemical Engineering Journal
- Accession number :
- edsair.doi...........22d08c36215f2971bb9005da616716ae
- Full Text :
- https://doi.org/10.1016/j.cej.2005.08.002