electronic nose odor classification with advanced decision tree structures

Clicks: 237
ID: 240470
2013
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Ranked #26 of 100 articles by views in molecular therapy : the journal of the american society of gene therapy

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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.
Reference Key
guney2013radioengineeringelectronic Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors ;S. Guney;A. Atasoy;R. Burget
Journal molecular therapy : the journal of the american society of gene therapy
Year 2013
DOI
DOI not found
URL
www.radioeng.cz/fulltexts/2013/13_03_0874_0882.pdf
Keywords
Machine learning electronic nose sensor systems electronics nuclear engineering

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