Classification of Agarwood using ANN

M. S., Najib and N. A., Mohd Ali and M. N., Mat Arip and M., Abd Jalil and M. N., Taib (2012) Classification of Agarwood using ANN. International Journal of Electrical and electronic Systems Research, 5. pp. 20-34. (Published)

[img] PDF
Classification_of_Agarwood_using_ANN.pdf - Published Version
Restricted to Repository staff only

Download (928kB) | Request a copy


An artifical neural network (ANN) has been modeled for the classification of Agarwood region. The target regions were from Melaka, Pagoh, Super Pagoh, Ulu Tembeling and Indonesia. The data analysis using Principal Component Analysis (PCA) was done to find significant input selection from 32 sensors of the E-nose and to recognize pattern variations from different number of Agarwood samples as inputs to ANN training. The network developed based on three layers feed forward network and the back propagation learning algorithm was used in executing the network training. Five input neurons, two hidden layer sizes and one output neurons were found to be the optimized combination for the network. The experimental results reveal that the proposed method is effective and significant to the classification of Agarwood region.

Item Type: Article
Uncontrolled Keywords: component; Agarwood, Classificastion, ANN.
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering
Faculty/Division: Faculty of Electrical & Electronic Engineering
Depositing User: Ms Suriati Mohd Adam
Date Deposited: 31 Dec 2014 03:30
Last Modified: 19 Apr 2018 01:18
Download Statistic: View Download Statistics

Actions (login required)

View Item View Item