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Data Clustering: Applications in Engineering (CROSBI ID 170594)

Prilog u časopisu | izvorni znanstveni rad | međunarodna recenzija

Krpić, Zdravko ; Martinović, Goran ; Vazler, Ivan Data Clustering: Applications in Engineering // Croatian operational research review, 1 (2010), 180-189

Podaci o odgovornosti

Krpić, Zdravko ; Martinović, Goran ; Vazler, Ivan

engleski

Data Clustering: Applications in Engineering

Dividing a set $S=\{; ; x_i=(x_1^{; ; (i)}; ; , x_2^{; ; (i)}; ; , \ldots, x_n^{; ; (i)}; ; )^T\in \mathbb{; ; R}; ; ^n\}; ; $ (a set of vectors from a vector space $\mathbb{; ; R}; ; ^n$) into disjunct subsets $\pi_1, \ldots, \pi_k$ $1\leq k\leq m$, such that \[ \bigcup\limits_{; ; i=1}; ; ^k \pi_i=S, \qquad \pi_i\cap \pi_j=\emptyset, \quad i\neq j, \qquad |\pi_j|\geq 1, \quad j=1, \dots, k, \] determines a partition of the set $S$ . The elements of such partition $\pi_1, \ldots, \pi_k$ 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.

data clustering; engineering; least squares

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Podaci o izdanju

1

2010.

180-189

objavljeno

1848-0225

1848-9931

Povezanost rada

Elektrotehnika, Matematika

Indeksiranost