A military conflict (especially its active phase) is a time of maximum exertion of all the powers of the state and society, a time that requires quick and correct decisions from state bodies. The quality of these decisions is largely determined by the estimation adequacy of the current situation. As the analysis shows, modern military conflicts start suddenly and develop rapidly. The official informing system turns out to be ineffective, what leads to numerous mistakes in decision-making. In addition, modern military conflicts are of a hybrid nature. The outcome of such military conflicts depends on many factors of a non-military nature, for example, the quality of governance, sup- port from the population, international assistance. These factors are often formulated qualitatively (linguistically), and the conditions of the active phase of a military conflict do not give time to check the adequacy of quantitative data. Therefore, it is necessary that the method for estimating the outcome of the active phase takes into account the data uncertainty and ensures a generalization of the partial characteristics of the current situation. Based on the analysis of known approaches to the description and process- ing of uncertainty, the authors proposed using the methods of fuzzy integral calculus to describe partial characteristics and calculate a generalized characteristic, which is an estimation of the success of the outcome of an active phase. The authors have solved the following subproblems: identification of structure and parameters of standard for estimating; choice of the observation channel of the characteristics of the current situation; constructing the algorithm for estimations generalization. The authors demonstrated the work of the proposed algorithm by the example of estimating the results of hostilities in eastern Ukraine in July 2014.
In this article the algorithm for the decision of alternatives' estimation problems for following conditions is considered. Values of alternative's characteristics (properties) are fuzzy. They are formalized as fuzzy sets. The estimation criteria structure is network-like and is formalized as the oriented graph with one source and many drains. The alternative's estimation result is calculated in criterion-source. Connections between criteria are formalized by fuzzy measures Sugeno. Upper-level criteria are considered as contexts for lower-level criteria. Fuzzy integrals Sugeno or Choquet are used as aggregation operator. In article also the properties of fuzzy measure and fuzzy integrals (Sugeno and Choquet) are analyzed. Properties of fuzzy measure and integrals are comparing with properties of other mathematical tools. As example the car's estimation problem is presented.
Keywords: model, international relations, fuzzy measure, political-economical risks
IntroductionThe dependence of investments risk into country from its international relations appreciably rises in conditions of globalization. The stability of international relations is especially important factor for investment into export-oriented industries of developed and post-soviet countries. The tense relations with neighboring states or states -world leaders in policy sphere or in safety sphere very often negatively influence export-import streams. Therefore the detailed studying and analysis of structure of international relations is today especially topical.The analysts evaluate the risk of investments into country by means of country-risk. The wellknown researches consider various aspects of country-risk. In (Bourke and Shanmugam, 1990), for example, the authors consider the country-risk as the risk that the country will be unable to service its external debt due to an inability to generate sufficient foreign exchange. The country risk model (www:\\riskmodel.eiu.com) calculates the country-risk as additive convolution along hierarchical system of financial, economic and political risk-categories: debt structure, fiscal policy, liquidity, political stability and others. This model includes the indicator
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