Performance prediction of tobacco flavouring using response surface methodology and artificial neural network

Performance prediction of tobacco flavouring using response surface methodology and artificial neural network

This study was to predict the optimum condition for leaf flavouring in cigarette manufacturing. To this purpose, an integrated research was used by using response surface and artificial neural network. A series of tobacco flavouring experiment's factors were designed by Experimental Design soft...

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Bibliographic Details
Main Authors: Lin Chen, Ruibo Yuan, Ze Liu
Format: Article
Language:English
Published: Wiley 2018-10-01
Series:The Journal of Engineering
Subjects:
response surface methodology
neural nets
design of experiments
tobacco industry
artificial neural network
cigarette manufacturing
tobacco flavouring experiment
Experimental Design software
MATLAB software
optimal solution configuration
Response Surface Analysis Method
roller speed
tobacco flow
spice ejector flow
response data
Expert Response Surface
tobacco process flow
feed liquid gas ejector flow
response surface design
pressure 3.7 bar
Online Access:https://digital-library.theiet.org/content/journals/10.1049/joe.2018.9038

Internet

https://digital-library.theiet.org/content/journals/10.1049/joe.2018.9038

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