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 gives quantitative effic...
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| Date: | 2010 |
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| Main Authors: | , |
| Format: | Article |
| Language: | English |
| Published: |
Інститут фізики напівпровідників імені В.Є. Лашкарьова НАН України
2010
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| Series: | Semiconductor Physics Quantum Electronics & Optoelectronics |
| Online Access: | http://dspace.nbuv.gov.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| Summary: | 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. |
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