Please use this identifier to cite or link to this item: http://elar.urfu.ru/handle/10995/83178
Title: Fuzzy Self-tuning Model for Analysis of Project Risks
Authors: Glushenko, S. A.
Doljenko, A. I.
Issue Date: 2018
Publisher: Knowledge E
Citation: Glushenko S. A. Fuzzy Self-tuning Model for Analysis of Project Risks / S. A. Glushenko, A. I. Doljenko // Russian Forum of Young Scientists (RFYS) (Ekaterinburg, Russia, 27–28 April , 2017). – Dubai : Knowledge E, 2018. – KnE Engineering, 3 (5). – pp. 271-279. – DOI 10.18502/keg.v3i4.2250
Abstract: The article states that risk management decision-making systems often operate on models of subject areas that are characterized by significant uncertainty. Traditional models of decision-making systems do not allow to take into consideration both quantitative and qualitative characteristics of objects in a complex manner. In addition, for the construction of traditional analytical, probable and simulation models, there is often no reliable data.The solution of these problems is proposed to be obtained on the basis of the theory of fuzzy sets. A fuzzy self-tuning model and its training approach is proposed, which assumes that presented sample is formed on the basis of the learning examples presented by sets of α-levels of fuzzy numbers.
URI: http://elar.urfu.ru/handle/10995/83178
Access: Creative Commons Attribution License
License text: https://creativecommons.org/licenses/by/4.0/
Conference name: Russian Forum of Young Scientists (RFYS)
Conference date: 27.04.2017-28.04.2017
ISSN: 2518-6841
DOI: 10.18502/keg.v3i4.2250
Sponsorship: This research has been carried out with financial support of RFBR within the framework of scientific project No. 16-31-00285 “Fuzzy logic methods and models in risk management decision support systems”.
Origin: Russian Forum of Young Scientists (RFYS). — Ekaterinburg, 2018
Appears in Collections:Междисциплинарные конференции, семинары, сборники

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