JACIII Vol.6 No.2 pp. 79-83
doi: 10.20965/jaciii.2002.p0079


Contribution to Creation of Complex System Macrosituations

Eva Ocelíková and Ladislav Madarász

Department of Cybernetics and Artificial Intelligence, Technical University of Kosice, Letná 9 04120 Kosice, Slovak Republic

July 2, 2002
August 2, 2002
June 20, 2002
situation control, macrosituation, attribute, classification, dimension reduction, principal component
This paper deals with the creation of multidimensional data classes – macrosituations – by decreasing their dimension. A large number of monitored attributes in examined situations in complex systems often complicates technical realization of classification and extends the time needed for providing a decision. It is possible to decrease the dimension of situations and, simultaneously, to not decrease decision-making quality. The main subject relates to a possible approach – the Principal Component Method. The basis of this method lies in finding a linear transformation of original p-dimensional space of attributes into a new p’-dimensional space of attributes where p’≤p. New attributes, called principal components, arise in a suitable linear combination of original attributes and are sorted in descending order based on their variance.
Cite this article as:
E. Ocelíková and L. Madarász, “Contribution to Creation of Complex System Macrosituations,” J. Adv. Comput. Intell. Intell. Inform., Vol.6 No.2, pp. 79-83, 2002.
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