Development of Correlations for Overall Gas Hold-up, Volumetric Mass Transfer Coefficient, and Effective Interfacial Area in Bubble Column Reactors Using Hybrid Genetic Algorithm-Support Vector Regression Technique: Viscous Newtonian and Non-Newtonian Liquids
Author:
Affiliation:
1. Institute of Chemical Technology, University of Mumbai, Matunga, Mumbai 400 019, India, and Chemical Engineering and Process Development Division, National Chemical Laboratory, Pune 411008, India
Publisher
American Chemical Society (ACS)
Subject
Industrial and Manufacturing Engineering,General Chemical Engineering,General Chemistry
Link
https://pubs.acs.org/doi/pdf/10.1021/ie801834w
Reference65 articles.
1. Artificial neural network approach for flow regime classification in gas–liquid–fiber flows based on frequency domain analysis of pressure signals
2. Development of an artificial neural network correlation for prediction of overall gas holdup in bubble column reactors
3. Soft-sensor development for fed-batch bioreactors using support vector regression
4. Development of support vector regression (SVR)-based correlation for prediction of overall gas hold-up in bubble column reactors for various gas–liquid systems
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