Powered by OpenAIRE graph
Found an issue? Give us feedback
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ http://cyberleninka....arrow_drop_down
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
addClaim

This Research product is the result of merged Research products in OpenAIRE.

You have already added 0 works in your ORCID record related to the merged Research product.

Применение теории нечетких множеств в анализе рисков инвестиционных проектов

Применение теории нечетких множеств в анализе рисков инвестиционных проектов

Abstract

Статья посвящена актуальной проблеме оценки сложных инвестиционных проектов в условиях риска и неопределенности. Рассматриваются основные методы учета рисков и подробно описываются их основные недостатки. В качестве альтернативного метода автором предлагается использование теории нечетких множеств, которая в последнее время становится все более популярна среди специалистов различного профиля. В статье показано, что теория нечетких множеств является одной из наиболее эффективных математических теорий, направленных на обработку неопределенной информации и во многом интегрирующей известные подходы и методы. Также автором была предложена математическая модель для расчета величины рисков инвестиционных проектов на основе теории нечеткости.

This article is consecrated on topical issues of the complicated capital spending projects valuation under risk and uncertainty. Also in this article considered main methods of risks tracking, and their central failures described in details. As an alternative method author offers using fuzzy sets theory, which became very popular recently among specialists of various prof. In this article is shown that fuzzy sets theory is one of the most effective mathematical theories, which directed to fuzzy information processing and in large measure integrates known approaches and methods. Also author offers numerical scheme for calculation of the amount of risks of capital spending projects at the nebulosity theory basis.

Keywords

ИНВЕСТИЦИИ, ОЦЕНКА СТОИМОСТИ, НЕЧЕТКИЕ МНОЖЕСТВА, УЧЕТ РИСКОВ, ДИСКОНТИРОВАНИЕ

  • BIP!
    Impact byBIP!
    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    0
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average