VGTU talpykla > Fundamentini┼│ moksl┼│ fakultetas / Faculty of Fundamental Sciences > Moksliniai straipsniai / Research articles >

Lietuvių   English
Please use this identifier to cite or link to this item:

Title: Scheme for Statistical Analysis of Some Parametric Normalization Classes
Authors: Krylovas, Aleksandras
Kosareva, Natalja
Zavadskas, Edmundas Kazimieras
Keywords: normalization methods
multi-criteria optimization
Monte Carlo method
comparative statistical analysis
Issue Date: 2018
Publisher: Agora University Press
Citation: Krylovas, A., Kosareva, N., & Zavadskas, E. (2018). Scheme for Statistical Analysis of Some Parametric Normalization Classes. INTERNATIONAL JOURNAL OF COMPUTERS COMMUNICATIONS & CONTROL, 13(6), 972-987. doi:10.15837/ijccc.2018.6.3398
Series/Report no.: 13;6
Abstract: In this research 7 parametric classes of normalization functions depending on 1 or 2 parameters proposed for MCDM problem solution. Monte Carlo experiments carried out to perform comparative statistical analysis and find optimal parameter values for the case of Gaussian distribution of decision making matrix elements. Optimal parameter values were ascertained for each normalization method. Normalization formulas were compared with each other in the sense of their efficiency. Logarithmic and Max normalization formulas demonstrated highest values of the best alternative identification. The proposed methodology of determining optimal parameter values of normalization formulas could be applied by approximation of real data with appropriate probability distributions.
ISSN: 1841-9844
1841-9836 ISSN-L
Appears in Collections:Moksliniai straipsniai / Research articles

Files in This Item:

File Description SizeFormat
Scheme for Statistical Analysis of Some Parametric Normalization Classes.pdf712.9 kBAdobe PDFView/Open

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.


Valid XHTML 1.0! DSpace Software Copyright © 2002-2010  Duraspace - Feedback