Title :
Application of ANN in agarwood oil grade classification
Author :
Ismail, Nur ; Rahiman, M.H.F. ; Taib, M.N. ; Ali, N.A.M. ; Jamil, M. ; Tajuddin, S.N.
Author_Institution :
Fac. of Electr. Eng., UiTM Shah Alam, Shah Alam, Malaysia
Abstract :
This paper presents the application of Artificial Neural Network (ANN) in agarwood oil grade classification. The work involved of the extraction of chemical compounds by GC-MS, identification the significant chemical compounds using Z-score, generating the synthetic data using a dedicated formulae and application of ANN classification. The ANN classification is performed and its performance is measured using accuracy, sensitivity and specificity. The result showed that the performance of ANN classification for original GC-MS data is increasing when the data is added with synthetic data. This study showed that the ANN application in this study required a large number of sample size for it to have high accuracy in classification.
Keywords :
chemical engineering computing; chemical technology; chromatography; essential oils; mass spectra; neural nets; production engineering computing; quality control; ANN classification; GC-MS; Z-score; agarwood oil grade classification; artificial neural network; chemical compounds; extraction; Accuracy; Artificial neural networks; Chemical compounds; Market research; Oils; Signal processing; Training; ANN; agarwood oil; chemical compounds; classification; grade;
Conference_Titel :
Signal Processing & its Applications (CSPA), 2014 IEEE 10th International Colloquium on
Conference_Location :
Kuala Lumpur
Print_ISBN :
978-1-4799-3090-6
DOI :
10.1109/CSPA.2014.6805751