2022
DOI: 10.1002/cjce.24344
|View full text |Cite
|
Sign up to set email alerts
|

Investigation of the drying kinetics of brewer's spent grain (BSG) using artificial neural networks and traditional empirical models

Abstract: Brewer's spent grain (BSG) is the main by‐product of the brewing industry. BSG can have diverse end‐users and has a high moisture level. To guarantee good conditions for storage and trade, it is necessary to remove the moisture from the material and use the proper method for the drying process. The phenomenon of water content removal is represented by mathematical models. Empirical and phenomenological models, as well as artificial neural networks (ANN) can be employed for this purpose. Here, we compare the fi… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

0
0
0

Year Published

2024
2024
2024
2024

Publication Types

Select...
1

Relationship

0
1

Authors

Journals

citations
Cited by 1 publication
references
References 35 publications
0
0
0
Order By: Relevance