Paper Info
Title
Scheme For Statistical Analysis Of Some Parametric Normalization Classes
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.
Year
DOI
Venue
2018
10.15837/ijccc.2018.6.3398
INTERNATIONAL JOURNAL OF COMPUTERS COMMUNICATIONS & CONTROL
Keywords
DocType
Volume
normalization methods, multi-criteria optimization, Monte Carlo method, comparative statistical analysis, SAW
Journal
13
Issue
ISSN
Citations 
6
1841-9836
0
PageRank 
References 
Authors
0.34
0
3
Name
Order
Citations
PageRank
Aleksandras Krylovas1262.96
Natalja Kosareva2393.29
Edmundas Kazimieras Zavadskas350049.88