TITLE
SUNFLOWER OIL QUALITY EVALUATION: A MULTISENSORY APPROACH USING AN ELECTRONIC OLFACTION SYSTEM
AUTHOR(S)
Todor Todorov, Stefan Ivanov, Toshko Nenov
ABSTRACT
The utilization of artificial neural networks (ANNs) for the precise classification of sunflower oil based on gas sensor responses is demonstrated in this study. Experimental data is collected through a cost-effective electronic nose featuring a gas sensor module. The trained ANN exhibits high precision in distinguishing different classes of sunflower oil.
DOI
http://www.doi.org/10.70456/PBVJ6260
DOWNLOAD
https://unitechsp.tugab.bg/images/2024/5-AR/s6_p27_v3.pdf
How to cite this article:
Todor Todorov, Stefan Ivanov, Toshko Nenov, SUNFLOWER OIL QUALITY EVALUATION: A MULTISENSORY APPROACH USING AN ELECTRONIC OLFACTION SYSTEM, UNITECH – SELECTED PAPERS - 2024