电子鼻
电子舌
主成分分析
舌头
线性判别分析
模式识别(心理学)
人工智能
鼻子
融合
数学
计算机科学
化学
医学
解剖
病理
语言学
哲学
食品科学
品味
作者
A. Zakaria,Ali Yeon Md Shakaff,Abdul Hamid Adom,Mardiana Idayu Ahmad,Maz Jamilah Masnan,Abdul Aziz,N. A. Fikri,Azizi Abdullah,Kamarulzaman Kamarudin
出处
期刊:Sensors
[MDPI AG]
日期:2010-09-28
卷期号:10 (10): 8782-8796
被引量:29
摘要
An improved classification of Orthosiphon stamineus using a data fusion technique is presented. Five different commercial sources along with freshly prepared samples were discriminated using an electronic nose (e-nose) and an electronic tongue (e-tongue). Samples from the different commercial brands were evaluated by the e-tongue and then followed by the e-nose. Applying Principal Component Analysis (PCA) separately on the respective e-tongue and e-nose data, only five distinct groups were projected. However, by employing a low level data fusion technique, six distinct groupings were achieved. Hence, this technique can enhance the ability of PCA to analyze the complex samples of Orthosiphon stamineus. Linear Discriminant Analysis (LDA) was then used to further validate and classify the samples. It was found that the LDA performance was also improved when the responses from the e-nose and e-tongue were fused together.
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