name
Krivko Mikhail Sergeevich
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Research interests
Математическая экономика
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Articles count: 2
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Description
This article focuses on crude oil trade development between Russian Federation and European Union with relation to port of Novorossiysk performance for the period of 2010-2015 taking into consideration restrictive measures imposed by European Union. Literature review on the topic of economic sanctions on Russia and other countries and impact of these measures on economy of these countries is given in the article. After analysis of crude oil trade volumes between Russia and European Union through port of Novorossiysk it is possible to conclude that decrease in crude oil trade started two years before the introduction of restrictive measures. Current values of international trade indicators can be under significant influence of sanctions, but the general trend of decline started before that, and this trend can be connected with other then political factors. Another conclusion is the fact that sanctions made an impact on growth of crude oil turnover, but at the same time this indicator was negative for almost a decade before, making it possible to consider the factor of sanctions as significant, but not decisive
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Description
The article presents an algorithm for constructing an expert system for quantitative bankruptcy risk estimation of small agricultural enterprises. Fuzzy logic analysis methodology in the form of fuzzy inference system was put as a basis for this development, classically including five steps: fuzzy rules base forming, fuzzification, aggregation, intensification, defuzzification. All the calculations were performed using MATLAB 2012 software package including Fuzzy module. Demand and costs of production were proposed as main factors influencing bankruptcy risk. Quantitative estimations of input parameters were determined by 100-point scale on the basis of expert estimations, and after that variables were fuzzificated in the form of trapezoid numbers as most common in fuzzy logic analysis (after triangular). Besides quantitative estimation of bankruptcy risk a surface of fuzzy inference was constructed, allowing to determine dependence between output variable’s values and input variables’ values of original bankruptcy risk model, as well as necessary values of input variables values to reach acceptable level by experts
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