Electronic Nose Odor Classification with Advanced Decision Tree Structures
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Date
2013-09
Authors
Guney, Selda
Atasoy, Ayten
Burget, Radim
ORCID
Advisor
Referee
Mark
Journal Title
Journal ISSN
Volume Title
Publisher
Společnost pro radioelektronické inženýrství
Abstract
Electronic nose (e-nose) is an electronic device which can measure chemical compounds in air and consequently classify different odors. In this paper, an e-nose device consisting of 8 different gas sensors was designed and constructed. Using this device, 104 different experiments involving 11 different odor classes (moth, angelica root, rose, mint, polis, lemon, rotten egg, egg, garlic, grass, and acetone) were performed. The main contribution of this paper is the finding that using the chemical domain knowledge it is possible to train an accurate odor classification system. The domain knowledge about chemical compounds is represented by a decision tree whose nodes are composed of classifiers such as Support Vector Machines and k-Nearest Neighbor. The overall accuracy achieved with the proposed algorithm and the constructed e-nose device was 97.18 %. Training and testing data sets used in this paper are published online.
Description
Citation
Radioengineering. 2013, vol. 22, č. 3, s. 874-882. issn 1210-2512
http://www.radioeng.cz/fulltexts/2013/13_03_0874_0882.pdf
http://www.radioeng.cz/fulltexts/2013/13_03_0874_0882.pdf
Document type
Peer-reviewed
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Published version
Date of access to the full text
Language of document
en