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Application of ANN in agarwood oil grade classification

机译:ANN在Agarwood油级分类中的应用

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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.
机译:本文介绍了人工神经网络(ANN)在Agarwood油级分类中的应用。通过GC-MS提取化学化合物所涉及的作品,使用Z分数鉴定显着的化学化合物,使用专用式和ANN分类的应用产生合成数据。进行ANN分类,使用精度,灵敏度和特异性测量其性能。结果表明,当数据添加合成数据时,原始GC-MS数据的ANN分类的性能正在增加。这项研究表明,本研究中的ANN应用需要大量的样本大小,以便在分类中具有高精度。

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