학술논문
Identification Of The Different Sources Responsible For The Olfactory Annoyance, Using An E-Nose.
Document Type
Article
Source
Subject
*OLFACTORY bulb
*ELECTRONIC noses
*MIXTURES
*SEWAGE disposal plants
*MACHINE learning
*SAMPLING (Process)
*PREDICTION models
*METAL oxide semiconductors
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Language
ISSN
0094-243X
Abstract
The aim of this work is to quantify mixtures of two complex odor sources, sampled in a waste treatment plant site, using a MOS-based e-nose. The study was performed in two steps: a learning phase, using samples of pure sources, followed by a validation phase with binary mixtures in known proportions. The results proved that the model developed was able to predict the ratio of each source involved in the mixture. [ABSTRACT FROM AUTHOR]