Application of fuzzy clustering and piezoelectric chemical sensor array for investigation on organic compounds

György Barkó, J. Abonyi, J. Hlavay

Research output: Contribution to journalArticle

38 Citations (Scopus)

Abstract

The fuzzy c-means (FCM) clustering models were used for the discrimination of organic compounds using piezoelectric chemical sensor array data of 14 analytes. Appropriate clusters are found by the sum of the weighted quadratic distances between data points and cluster prototypes. A priori known information can be integrated into the clustering algorithm by using constrained prototypes. A sensor array was built using piezoelectric quartz crystal sensors. Four AT-cut quartz crystals with 9MHz fundamental frequencies were applied. Sensing materials were OV1, OV275, ASI50, and polyphenil-ether. The appropriate coating materials were found by principal component analysis. The application of the fuzzy clustering method has been proved to be a reliable way of identifying similar, pure organic compounds. Copyright (C) 1999 Elsevier Science B.V.

Original languageEnglish
Pages (from-to)219-226
Number of pages8
JournalAnalytica Chimica Acta
Volume398
Issue number2-3
DOIs
Publication statusPublished - Oct 22 1999

Fingerprint

Quartz
Fuzzy clustering
Sensor arrays
Chemical sensors
Organic compounds
Cluster Analysis
organic compound
sensor
Crystals
Clustering algorithms
Ether
Principal component analysis
crystal
quartz
Principal Component Analysis
ether
Coatings
coating
principal component analysis
Sensors

Keywords

  • Chemical sensor array
  • Classification
  • Fuzzy algorithm
  • Volatile organic compounds

ASJC Scopus subject areas

  • Biochemistry
  • Analytical Chemistry
  • Spectroscopy
  • Environmental Chemistry

Cite this

Application of fuzzy clustering and piezoelectric chemical sensor array for investigation on organic compounds. / Barkó, György; Abonyi, J.; Hlavay, J.

In: Analytica Chimica Acta, Vol. 398, No. 2-3, 22.10.1999, p. 219-226.

Research output: Contribution to journalArticle

@article{33b4f60b73b24d3fa235f152e8032acc,
title = "Application of fuzzy clustering and piezoelectric chemical sensor array for investigation on organic compounds",
abstract = "The fuzzy c-means (FCM) clustering models were used for the discrimination of organic compounds using piezoelectric chemical sensor array data of 14 analytes. Appropriate clusters are found by the sum of the weighted quadratic distances between data points and cluster prototypes. A priori known information can be integrated into the clustering algorithm by using constrained prototypes. A sensor array was built using piezoelectric quartz crystal sensors. Four AT-cut quartz crystals with 9MHz fundamental frequencies were applied. Sensing materials were OV1, OV275, ASI50, and polyphenil-ether. The appropriate coating materials were found by principal component analysis. The application of the fuzzy clustering method has been proved to be a reliable way of identifying similar, pure organic compounds. Copyright (C) 1999 Elsevier Science B.V.",
keywords = "Chemical sensor array, Classification, Fuzzy algorithm, Volatile organic compounds",
author = "Gy{\"o}rgy Bark{\'o} and J. Abonyi and J. Hlavay",
year = "1999",
month = "10",
day = "22",
doi = "10.1016/S0003-2670(99)00377-3",
language = "English",
volume = "398",
pages = "219--226",
journal = "Analytica Chimica Acta",
issn = "0003-2670",
publisher = "Elsevier",
number = "2-3",

}

TY - JOUR

T1 - Application of fuzzy clustering and piezoelectric chemical sensor array for investigation on organic compounds

AU - Barkó, György

AU - Abonyi, J.

AU - Hlavay, J.

PY - 1999/10/22

Y1 - 1999/10/22

N2 - The fuzzy c-means (FCM) clustering models were used for the discrimination of organic compounds using piezoelectric chemical sensor array data of 14 analytes. Appropriate clusters are found by the sum of the weighted quadratic distances between data points and cluster prototypes. A priori known information can be integrated into the clustering algorithm by using constrained prototypes. A sensor array was built using piezoelectric quartz crystal sensors. Four AT-cut quartz crystals with 9MHz fundamental frequencies were applied. Sensing materials were OV1, OV275, ASI50, and polyphenil-ether. The appropriate coating materials were found by principal component analysis. The application of the fuzzy clustering method has been proved to be a reliable way of identifying similar, pure organic compounds. Copyright (C) 1999 Elsevier Science B.V.

AB - The fuzzy c-means (FCM) clustering models were used for the discrimination of organic compounds using piezoelectric chemical sensor array data of 14 analytes. Appropriate clusters are found by the sum of the weighted quadratic distances between data points and cluster prototypes. A priori known information can be integrated into the clustering algorithm by using constrained prototypes. A sensor array was built using piezoelectric quartz crystal sensors. Four AT-cut quartz crystals with 9MHz fundamental frequencies were applied. Sensing materials were OV1, OV275, ASI50, and polyphenil-ether. The appropriate coating materials were found by principal component analysis. The application of the fuzzy clustering method has been proved to be a reliable way of identifying similar, pure organic compounds. Copyright (C) 1999 Elsevier Science B.V.

KW - Chemical sensor array

KW - Classification

KW - Fuzzy algorithm

KW - Volatile organic compounds

UR - http://www.scopus.com/inward/record.url?scp=0032847589&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0032847589&partnerID=8YFLogxK

U2 - 10.1016/S0003-2670(99)00377-3

DO - 10.1016/S0003-2670(99)00377-3

M3 - Article

AN - SCOPUS:0032847589

VL - 398

SP - 219

EP - 226

JO - Analytica Chimica Acta

JF - Analytica Chimica Acta

SN - 0003-2670

IS - 2-3

ER -