Proceedings of the 2013 International Conference on Advances in Intelligent Systems in Bioinformatics

Fusion Technique for Honey Purity Estimation using Artificial Neural Network

Authors
Norazian Subari, Junita Mohamad Saleh, Ali Yeon Md Shakaff
Corresponding Author
Norazian Subari
Available Online January 2014.
Keywords
E-nose, FTIR, Fusion, Artifi-cial Neural Network
Abstract
This paper presents the estimation of pu-rity of honey using Artificial Neural Network (ANN). ANN method was used to automate the decision of estimation, replacing the manual human approximate method. A total of 21 honey purity sam-ples from various concentrations of pure honey, adulterated honey and pure sugar were collected. The data were collected using electronic nose (E-nose) and Fouri-er Transform Infrared (FTIR). Fusion method was applied in this work by com-bining the variable from both E-nose and FTIR to produce new sets of data. This data were used as input parameters for ANN learning. The results show that ANN was able to estimate the concentra-tion of honey purity in adulterated honey solution with less error using fusion data as compared to single modality data.
Open Access
This is an open access article distributed under the CC BY-NC license.

Download article (PDF)

Volume Title
Proceedings of the 2013 International Conference on Advances in Intelligent Systems in Bioinformatics
Series
Advances in Intelligent Systems Research
Publication Date
January 2014
ISBN
978-94-6252-000-4
ISSN
1951-6851
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Norazian Subari
AU  - Junita Mohamad Saleh
AU  - Ali Yeon Md Shakaff
PY  - 2014/01
DA  - 2014/01
TI  - Fusion Technique for Honey Purity Estimation using Artificial Neural Network
BT  - Proceedings of the 2013 International Conference on Advances in Intelligent Systems in Bioinformatics
PB  - Atlantis Press
SP  - 40
EP  - 46
SN  - 1951-6851
UR  - https://www.atlantis-press.com/article/11355
ID  - Subari2014/01
ER  -