About: Electronic Nose Odor Classification with Advanced Decision Tree Structures

Facets (new session)
Description
Metadata
Settings
- owl:sameAs
- Inference Rule:

About: Electronic Nose Odor Classification with Advanced Decision Tree Structures Goto Sponge NotDistinct Permalink

An Entity of Type : http://linked.opendata.cz/ontology/domain/vavai/Vysledek, within Data Space : linked.opendata.cz associated with source document(s)

Attributes	Values
rdf:type	skos:Concept http://linked.opendata.cz/ontology/domain/vavai/Vysledek
Description	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 -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 onlin 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 -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 onlin (en)
Title	Electronic Nose Odor Classification with Advanced Decision Tree Structures Electronic Nose Odor Classification with Advanced Decision Tree Structures (en)
skos:prefLabel	Electronic Nose Odor Classification with Advanced Decision Tree Structures Electronic Nose Odor Classification with Advanced Decision Tree Structures (en)
skos:notation	RIV/00216305:26220/13:PU104555!RIV14-MPO-26220___
http://linked.open...avai/predkladatel	Fakulta elektrotechniky a komunikačních technologií
http://linked.open...avai/riv/aktivita	P
http://linked.open...avai/riv/aktivity	P(FR-TI4/151)
http://linked.open...iv/cisloPeriodika	1
http://linked.open...vai/riv/dodaniDat	2014
http://linked.open...aciTvurceVysledku	Burget, Radim
http://linked.open.../riv/druhVysledku	J - Článek v odborném periodiku
http://linked.open...iv/duvernostUdaju	S - Úplné a pravdivé údaje nepodléhající ochraně podle zvláštních právních předpisů
http://linked.open...titaPredkladatele	Vysoké učení technické v Brně / Fakulta elektrotechniky a komunikačních technologií
http://linked.open...dnocenehoVysledku	72426
http://linked.open...ai/riv/idVysledku	RIV/00216305:26220/13:PU104555
http://linked.open...riv/jazykVysledku	eng - angličtina
http://linked.open.../riv/klicovaSlova	Electronic nose, odor classification, machine learning, data-mining. (en)
http://linked.open.../riv/klicoveSlovo	Electronic nose data-mining. odor classification machine learning
http://linked.open...odStatuVydavatele	CZ - Česká republika
http://linked.open...ontrolniKodProRIV	[7995C16F7E4B]
http://linked.open...i/riv/nazevZdroje	Radioengineering
http://linked.open...in/vavai/riv/obor	BD
http://linked.open...ichTvurcuVysledku	1 (xsd:int)
http://linked.open...cetTvurcuVysledku	3 (xsd:int)
http://linked.open...vavai/riv/projekt	Výzkum a vývoj technologie pro detekci emocí v nestrukturovaných datech
http://linked.open...UplatneniVysledku	2013
http://linked.open...v/svazekPeriodika	2011
http://linked.open...iv/tvurceVysledku	Burget, Radim Atasoy, Ayten Güney, Selda
issn	1210-2512
number of pages	9 (xsd:int)
http://localhost/t...ganizacniJednotka	26220

Faceted Search & Find service v1.16.118 as of Jun 21 2024

Alternative Linked Data Documents: ODE Content Formats:

RDF

ODATA

Microdata

About

OpenLink Virtuoso version 07.20.3240 as of Jun 21 2024, on Linux (x86_64-pc-linux-gnu), Single-Server Edition (126 GB total memory, 58 GB memory in use)
Data on this page belongs to its respective rights holders.
Virtuoso Faceted Browser Copyright © 2009-2024 OpenLink Software