NDLI: Classification and Quantification of Binary Mixtures of Gases/Odors Using Thick-Film Gas Sensor Array Responses

Content Provider	IEEE Xplore Digital Library
Author	Sunny Kumar, V. Mishra, V.N. Dwivedi, R. Das, R.R.
Copyright Year	2001
Abstract	This paper presents the results of experiments done for classification and quantification of two volatile organic compounds (VOCs), namely, acetone (CH₃COCH₃) and 2-Propanol (CH₃CHOHCH₃) in their single as well as in mixture forms. A sensor array consisting of four sensor elements was fabricated in our lab using thick-film fabrication technology. The steady-state responses of the sensor array were collected for the mentioned VOCs in their single as well as in mixture form. A hierarchical system consisting of gating network and three quantification networks was designed to classify and subsequently quantify the individual and mixture of VOCs. The classification accuracy results of gating network have been ensured using back-propagation neural network (BPNN) and support vector machine (SVM). For quantification multioutput support vector regression method was used in slave networks for single as well as binary mixture data. k-fold cross validation scheme was adopted for all the experiments. The average classification accuracy of gating network for the mixture data in raw form was 89.5% using BPNN and 94.7% using nu-SVM. With principal component analysis preprocessed data, the average accuracy was 95.6% with BPNN and 100% using nu-SVM, respectively. For quantification, good 0.9828 and 0.9764 correlation coefficients for the predicted versus real concentration of acetone and 2-Propanol, respectively, in mixture form were obtained. Thus, we report a promising approach for binary mixture of gases/odors analysis using thick-film gas sensor array responses.
Sponsorship	IEEE Sensors Council
Starting Page	1252
Ending Page	1260
Page Count	9
File Size	1686207
File Format	PDF
ISSN	1530437X
Volume Number	15
Issue Number	2
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-01-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Gases Principal component analysis Support vector machines Gas detectors Sensor arrays thick film Binary gas mixture gas sensor array neural classifier support vector machine quantification
Content Type	Text
Resource Type	Article
Subject	Instrumentation Electrical and Electronic Engineering

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Classification of Gases/Odors Using Dynamic Responses of Thick Film Gas Sensor Array

Quantification of Individual Gases/Odors Using Dynamic Responses of Gas Sensor Array With ASM Feature Technique

Role of Exposure and Recovery Transients in Classification of Gases/Odors With Thick Film Sensor Array

Gases/Odors Identification With Artificial Immune Recognition System Using Thick Film Gas Sensor Array Responses

A fuzzy logic based neural network classifier for qualitative classification of odors/gases

Gas quantitative analysis with support vector machine

Wavelet Coefficient Trained Neural Network Classifier for Improvement in Qualitative Classification Performance of Oxygen-Plasma Treated Thick Film Tin Oxide Sensor Array Exposed to Different Odors/Gases

Gas classification using binary decision tree classifier

A Reduced Complexity Two-Stage Neural Classifier for Quantified Identification of Gases/Odors Using an Integrated Thick Film Sensor Array

Classification and Quantification of Binary Mixtures of Gases/Odors Using Thick-Film Gas Sensor Array Responses

Similar Documents

Classification of Gases/Odors Using Dynamic Responses of Thick Film Gas Sensor Array

Quantification of Individual Gases/Odors Using Dynamic Responses of Gas Sensor Array With ASM Feature Technique

Role of Exposure and Recovery Transients in Classification of Gases/Odors With Thick Film Sensor Array

Gases/Odors Identification With Artificial Immune Recognition System Using Thick Film Gas Sensor Array Responses

A fuzzy logic based neural network classifier for qualitative classification of odors/gases

Gas quantitative analysis with support vector machine

Wavelet Coefficient Trained Neural Network Classifier for Improvement in Qualitative Classification Performance of Oxygen-Plasma Treated Thick Film Tin Oxide Sensor Array Exposed to Different Odors/Gases

Gas classification using binary decision tree classifier

A Reduced Complexity Two-Stage Neural Classifier for Quantified Identification of Gases/Odors Using an Integrated Thick Film Sensor Array

Classification and Quantification of Binary Mixtures of Gases/Odors Using Thick-Film Gas Sensor Array Responses