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Izvorni znanstveni članak
DATA CLUSTERING: APPLICATIONS IN ENGINEERING
Zdravko Krpić
; Faculty of Electrical Engineering, University of Osijek, Osijek, Croatia
Goran Martinović
orcid.org/0000-0002-7469-6018
; Faculty of Electrical Engineering, University of Osijek, Osijek, Croatia
Ivan Vazler
; Department of Mathematics, University of Osijek, Osijek, Croatia
| Puni tekst: engleski, pdf (520 KB) | str. 180-189 | citiraj | |
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APA 6th Edition Krpić, Z., Martinović, G. i Vazler, I. (2010). DATA CLUSTERING: APPLICATIONS IN ENGINEERING. Croatian Operational Research Review, 1 (1), 180-189. Preuzeto s https://hrcak.srce.hr/94967 MLA 8th Edition Krpić, Zdravko, et al. "DATA CLUSTERING: APPLICATIONS IN ENGINEERING." Croatian Operational Research Review, vol. 1, br. 1, 2010, str. 180-189. https://hrcak.srce.hr/94967. Citirano 26.09.2021. Chicago 17th Edition Krpić, Zdravko, Goran Martinović i Ivan Vazler. "DATA CLUSTERING: APPLICATIONS IN ENGINEERING." Croatian Operational Research Review 1, br. 1 (2010): 180-189. https://hrcak.srce.hr/94967 Harvard Krpić, Z., Martinović, G., i Vazler, I. (2010). 'DATA CLUSTERING: APPLICATIONS IN ENGINEERING', Croatian Operational Research Review, 1(1), str. 180-189. Preuzeto s: https://hrcak.srce.hr/94967 (Datum pristupa: 26.09.2021.) Vancouver Krpić Z, Martinović G, Vazler I. DATA CLUSTERING: APPLICATIONS IN ENGINEERING. Croatian Operational Research Review [Internet]. 2010 [pristupljeno 26.09.2021.];1(1):180-189. Dostupno na: https://hrcak.srce.hr/94967 IEEE Z. Krpić, G. Martinović i I. Vazler, "DATA CLUSTERING: APPLICATIONS IN ENGINEERING", Croatian Operational Research Review, vol.1, br. 1, str. 180-189, 2010. [Online]. Dostupno na: https://hrcak.srce.hr/94967. [Citirano: 26.09.2021.] |
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Sažetak
Dividing a set S $\mathcal{S} = \{x_i=(x_1^{(i)}+\dots+x_n^{(i)})^T \in \mathbb{R}^n:i=1,\dots,m\}$ (a set of vectors from a vector space $\mathbb{R}^n$) into disjunct subsets $\pi_1,\dots,\pi_k, 1\leq k\leq m$, such that
$\cup_{i=1}^k \pi_i=S,
\pi_i \cap \pi_j=0, i \ne j,
|\pi_j|\geq 1, j=1,\dots,k$,
determines a partition of the set $\mathcal{S}$. The elements of such partition $\pi_1,\dots,\pi_k$ are called clusters.
For practical clustering applications the number of all clusters is too big and the problem of determining the optimal partition in the least-squares sense is an NP-hard problem.
In this paper we will consider some well-known algorithms for searching for an optimal LS-partition, list some of the numerous applications of cluster analysis in engineering and give some practical applications.
Ključne riječi
data clustering; engineering; least squares
Hrčak ID: 94967
URI
https://hrcak.srce.hr/94967
Moj profil
Srce