Artificial Intelligence and Decision Making
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Artificial Intelligence and Decision Making, 2018, Issue 2, Pages 95–102
DOI: https://doi.org/10.14357/20718594180208
(Mi iipr210)
 

Decision analysis

About the limits of applicability of the analytical network process in the decision-making problems in the natural sciences

K. A. Seredkin

P. P. Shirshov Institute of Oceanology, Russian Academy of Sciences, Moscow, Russia
Abstract: The article reviews the concept, features, some of the key points and drawbacks of the analytical network process (ANP) for decision-making problems. It examines one of the key issues of the ANP – the problem of cycles and methods of its decision which are based on the experimental data. On the basis of these ones is formed the author’s view of the networks classification. It is inferred about the applicability of ANP for different types of networks for solution of scientific and some other kinds of applied tasks. For datasets that are unsuitable for processing by ANP is offered a different path, which consists in using the method of direct influences, developed by a group of scientists with participation of the author on the basis of the analytical networks concept as ANP alternatives. The offered path is also used for tasks that do not fall within the scope of ANP.
Keywords: system analysis, analytical networks, network approach, analytic network process, ANP, T. Saati, method of direct influence.
Bibliographic databases:
Document Type: Article
Language: Russian
Citation: K. A. Seredkin, “About the limits of applicability of the analytical network process in the decision-making problems in the natural sciences”, Artificial Intelligence and Decision Making, 2018, no. 2, 95–102
Citation in format AMSBIB
\Bibitem{Ser18}
\by K.~A.~Seredkin
\paper About the limits of applicability of the analytical network process in the decision-making problems in the natural sciences
\jour Artificial Intelligence and Decision Making
\yr 2018
\issue 2
\pages 95--102
\mathnet{http://mi.mathnet.ru/iipr210}
\crossref{https://doi.org/10.14357/20718594180208}
\elib{https://elibrary.ru/item.asp?id=35125461}
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