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- W854994554 abstract "We have been designed and constructed an artificial odour recognition system(electronic nose system) using metal oxide type sensor array for recognizing and analyzing various odours. We proposed an unsupervised clustering method based on Euclidean distances in order for human observer to examine easily multi-dimensional data, which has been measured from an array of sensors. This is a combination of Principal Components Analysis(PCA) used as a starting point for Sammom Mapping Method(SMM). No prior assumptions are made of the classes in which odour belong, and the error due to dimensional reduction at the PCA can be minimized without the disadvantages of rotation of clusters when the order of data sets in a data base was changed in the SMM. An artificial odour recognition system with the proposed unsupervised clustering method was applied to assessment of odour differences of Volatile Organic Compounds(VOCs) and Korean whiskies respectively, and demonstrated the best performances throughout the experimental trails." @default.
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- W854994554 date "2001-01-01" @default.
- W854994554 modified "2023-09-23" @default.
- W854994554 title "Implementation of an Artificial Odour Recognition System with Unsupervised Clustering Methods" @default.
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