Naslov
Data Clustering: Applications in Engineering

Autori
Krpić, Zdravko ; Martinović, Goran ; Vazler, Ivan

Izvornik
Croatian operational research review (1848-0225) 1 (2010); 180-189

Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni

Ključne riječi
data clustering; engineering; least squares

Sažetak
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.

Izvorni jezik
Engleski

Znanstvena područja
Matematika, Elektrotehnika

POVEZANOST RADA