Please use this identifier to cite or link to this item:https://hdl.handle.net/20.500.12259/37465
Type of publication: research article
Type of publication (PDB): Straipsnis Clarivate Analytics Web of Science / Article in Clarivate Analytics Web of Science (S1)
Field of Science: Informatika / Informatics (N009)
Author(s): Varoneckas, Audrius;Žilinskas, Antanas;Žilinskas, Julius
Title: Parallel multidimensional scaling using grid computing : assesment of performance
Is part of: Informacinės technologijos ir valdymas = Information technology and control. Kaunas : Technologija, 2008, Vol. 37, no. 1
Extent: p. 52-56
Date: 2008
Keywords: GRID skaičiavimai;Daugiamatės skalės;Algoritmai, genetiniai;Grid computing;Multidimensional scaling;Algorithm, evolutionary
Abstract: Multidimensional scaling is a technique for visualization and exploratory analysis of multidimensional data aiming to discover a structure of sets of objects using information on similarities/dissimilarities between those objects. A difficult global optimization problem should be solved to minimize the error of visualization. A hybrid optimization algorithm has been constructed combining evolutionary global search with efficient local descent. A parallel version of the proposed optimization algorithm is implemented to enable solution of large scale problems in acceptable time. In the present paper we investigated the efficiency of the parallel version of the algorithm on PC clusters and computational grids
Internet: http://itc.ktu.lt/index.php/ITC/article/view/11929/6596
Affiliation(s): Informatikos fakultetas
Kauno medicinos universiteto Psichofiziologijos ir reabilitacijos institutas
Matematikos ir informatikos institutas
Vytauto Didžiojo universitetas
Appears in Collections:Universiteto mokslo publikacijos / University Research Publications

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