An Intelligent E-Nose System For Discrimination Of Alcholic Odorants
نویسنده
چکیده
Abstract: This paper presents a neural network classifier for classification of individual wine odors. The data set used for classification was obtained from already reported responses of thick-film tin oxide sensor array exposed to five different alcoholic beverages. The proposed classifier was trained with back-propagation algorithm and fuzzy memberships were used as target vectors in the output feature space. Transformed Cluster Analysis (TCA) was used as a data pre-processing technique and it was observed that pre-processing the sensor output data with TCA significantly enhances the classification capability and the error performance of the proposed neuro-fuzzy classifier.
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