Methods of cluster analysis in sensor engineering: advantages and faults

We consider the crisp and fuzzy partitioning techniques of cluster analysis
 bearing in mind their application for classification of data obtained with chemical sensor
 arrays. The advantage of the cluster analysis techniques is existence of a parameter S(i).
 This parameter...

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Published in:Semiconductor Physics Quantum Electronics & Optoelectronics
Date:2010
Main Authors: Burlachenko, Yu.V., Snopok, B.A.
Format: Article
Language:English
Published: Інститут фізики напівпровідників імені В.Є. Лашкарьова НАН України 2010
Online Access:https://nasplib.isofts.kiev.ua/handle/123456789/118565
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Journal Title:Digital Library of Periodicals of National Academy of Sciences of Ukraine
Cite this:Methods of cluster analysis in sensor engineering:
 advantages and faults / Yu.V. Burlachenko, B.A. Snopok // Semiconductor Physics Quantum Electronics & Optoelectronics. — 2010. — Т. 13, № 4. — С. 393-397. — Бібліогр.: 13 назв. — англ.

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Digital Library of Periodicals of National Academy of Sciences of Ukraine
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author Burlachenko, Yu.V.
Snopok, B.A.
author_facet Burlachenko, Yu.V.
Snopok, B.A.
citation_txt Methods of cluster analysis in sensor engineering:
 advantages and faults / Yu.V. Burlachenko, B.A. Snopok // Semiconductor Physics Quantum Electronics & Optoelectronics. — 2010. — Т. 13, № 4. — С. 393-397. — Бібліогр.: 13 назв. — англ.
collection DSpace DC
container_title Semiconductor Physics Quantum Electronics & Optoelectronics
description We consider the crisp and fuzzy partitioning techniques of cluster analysis
 bearing in mind their application for classification of data obtained with chemical sensor
 arrays. The advantage of the cluster analysis techniques is existence of a parameter S(i).
 This parameter gives quantitative efficiency of classification and can be used as
 optimization criterion for sensor system as a whole as well as the measurement
 procedure. The crisp and fuzzy techniques give practically the same result when
 analyzing the data that cluster uniquely. It is shown that big value of the parameter S(i) is
 not sufficient for adequate data partitioning into cluster in more complicated cases, and
 the results of clusterization for the above techniques may diverge. In this case, one
 should apply both techniques concurrently, checking the correctness of partitioning into
 clusters against the principal component analysis.
first_indexed 2025-11-28T12:05:05Z
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institution Digital Library of Periodicals of National Academy of Sciences of Ukraine
issn 1560-8034
language English
last_indexed 2025-11-28T12:05:05Z
publishDate 2010
publisher Інститут фізики напівпровідників імені В.Є. Лашкарьова НАН України
record_format dspace
spelling Burlachenko, Yu.V.
Snopok, B.A.
2017-05-30T16:19:45Z
2017-05-30T16:19:45Z
2010
Methods of cluster analysis in sensor engineering:
 advantages and faults / Yu.V. Burlachenko, B.A. Snopok // Semiconductor Physics Quantum Electronics & Optoelectronics. — 2010. — Т. 13, № 4. — С. 393-397. — Бібліогр.: 13 назв. — англ.
1560-8034
PACS 07.07.Df
https://nasplib.isofts.kiev.ua/handle/123456789/118565
We consider the crisp and fuzzy partitioning techniques of cluster analysis
 bearing in mind their application for classification of data obtained with chemical sensor
 arrays. The advantage of the cluster analysis techniques is existence of a parameter S(i).
 This parameter gives quantitative efficiency of classification and can be used as
 optimization criterion for sensor system as a whole as well as the measurement
 procedure. The crisp and fuzzy techniques give practically the same result when
 analyzing the data that cluster uniquely. It is shown that big value of the parameter S(i) is
 not sufficient for adequate data partitioning into cluster in more complicated cases, and
 the results of clusterization for the above techniques may diverge. In this case, one
 should apply both techniques concurrently, checking the correctness of partitioning into
 clusters against the principal component analysis.
This work got a financial support from the National
 Academy of Sciences of Ukraine.
en
Інститут фізики напівпровідників імені В.Є. Лашкарьова НАН України
Semiconductor Physics Quantum Electronics & Optoelectronics
Methods of cluster analysis in sensor engineering: advantages and faults
Article
published earlier
spellingShingle Methods of cluster analysis in sensor engineering: advantages and faults
Burlachenko, Yu.V.
Snopok, B.A.
title Methods of cluster analysis in sensor engineering: advantages and faults
title_full Methods of cluster analysis in sensor engineering: advantages and faults
title_fullStr Methods of cluster analysis in sensor engineering: advantages and faults
title_full_unstemmed Methods of cluster analysis in sensor engineering: advantages and faults
title_short Methods of cluster analysis in sensor engineering: advantages and faults
title_sort methods of cluster analysis in sensor engineering: advantages and faults
url https://nasplib.isofts.kiev.ua/handle/123456789/118565
work_keys_str_mv AT burlachenkoyuv methodsofclusteranalysisinsensorengineeringadvantagesandfaults
AT snopokba methodsofclusteranalysisinsensorengineeringadvantagesandfaults