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Моделирование динамики рыночной системы

Моделирование динамики рыночной системы

Abstract

In the modern conditions of dynamic development of the market system, the economy, feeling polynomial enthusiasm and recessions, demands external influence, regulation, management. It isn't possible to realize an effective control system of economy without understanding of a consequence. The regulating structure represented by the state needs an effective system of the support of decision-making allowing to estimate the consequences of the made decisions before their direct realization. Use of modern methods of complex estimation for modeling of market system on the basis of trees of criteria and matrixes of convolution allows forming a static market model in the form of the functions of sensitivity interpreted as curves of supply and demand. However, the questions of creation of dynamic market system on the basis of these mechanisms weren't discussed so far. In this article the questions of possibility of modeling of dynamics of the market system built on the basis of mechanisms of complex estimation are discussed. Relevance of the chosen method depends on the possibility of preliminary formation of possible outcomes of an event in the form of the count on definition further of probability of transition to each of states on the basis of a complex assessment of the individual of "advantage" of such transition. An additional benefit of such approach is that fact that when forming market system from some contingent of participants with different behavior models for each of them there is an opportunity to create the scenario, and when receiving at a stage of modeling of result to reconsider the new created structure of structure of society

В современных условиях динамичного развития рыночной системы экономика, испытывающая многочленные подъёмы и спады, требует внешнего воздействия, регулирования, управления. Реализовать эффективную систему управления экономикой без понимания последствия не представляется возможным. Регулирующая структура в лице государства нуждается в эффективной системе поддержки принятия решений, позволяющей оценить последствия принимаемых решений до их непосредственной реализации. Использование современных методов комплексного оценивания для моделирования рыночной системы на основе деревьев критериев и матриц свёртки позволяет формировать статическую модель рынка в виде функций чувствительности, интерпретируемых как кривые спроса и предложения. Однако, до настоящего времени не обсуждались вопросы построения динамической рыночной системы на основе данных механизмов. В статье обсуждаются вопросы возможности моделирования динамики рыночной системы, выстроенной на основе механизмов комплексного оценивания. Актуальность выбранного метода определяется возможностью предварительного формирования возможных исходов события в виде графа с определением в дальнейшем вероятности перехода к каждому из состояний, на основе комплексной оценки индивида «выгодности» такого перехода. Дополнительным преимуществом такого подхода является тот факт, что при формировании рыночной системы из некоторого контингента участников с разными моделями поведения для каждого из них имеется возможность сформировать свой сценарий, а при получении на этапе моделирования результата пересмотреть новый сформированный состав структуры социума

Keywords

РЫНОК,РЫНОЧНАЯ СИСТЕМА,МОДЕЛИРОВАНИЕ ПОВЕДЕНИЯ,ДИНАМИЧЕСКАЯ СИСТЕМА,СОЦИАЛЬНО-ЭКОНОМИЧЕСКАЯ СИСТЕМА,ЦЕПИ МАРКОВА,ВЕРОЯТНОСТЬ ПЕРЕХОДА,СМЕНА СОСТОЯНИЯ,MARKET,MARKET SYSTEM,BEHAVIOR MODELING,DYNAMIC SYSTEM,SOCIO-ECONOMIC SYSTEM,MARKOV CHAIN,TRANSITION PROBABILITY,CHANGE OF STATE

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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
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