Fusion Technique for Honey Purity Estimation using Artificial Neural Network
Norazian Subari, Junita Mohamad Saleh, Ali Yeon Md Shakaff
Available Online January 2014.
- E-nose, FTIR, Fusion, Artifi-cial Neural Network
- 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.
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 -