Mathematical Models in the Risk Assessment in the Decision-Making Process
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2023-12-07 16:45
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BULAT, Inga. Mathematical Models in the Risk Assessment in the Decision-Making Process. In: Conference on Applied and Industrial Mathematics: CAIM 2017, 14-17 septembrie 2017, Iași. Chișinău: Casa Editorial-Poligrafică „Bons Offices”, 2017, Ediţia 25, p. 29. ISBN 978-9975-76-247-2.
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Conference on Applied and Industrial Mathematics
Ediţia 25, 2017
Conferința "Conference on Applied and Industrial Mathematics"
Iași, Romania, 14-17 septembrie 2017

Mathematical Models in the Risk Assessment in the Decision-Making Process


Pag. 29-29

Bulat Inga
 
Academy of Sciences of Moldova
 
 
Disponibil în IBN: 23 septembrie 2022


Rezumat

At present, risk analysis in decision-making is management discipline, which establishes a connection with mathematics and computing that deals with substantiating decision-making in terms of eciency in the economic and nancial eld. The modeling of a decision-making process under conditions of uncertainty leads us to specify its elements, namely: the risk, the problem formulation and the speci cation of the minimization / maximization objectives of certain technical and economic indicators, the variety of possible varieties / alternatives that characterize a decisional situation, the set of anticipated consequences For each variant; - independent factors of decisionmakers and of short-term type. Of the set of possible variants, it is calculated by a method or several mathematical methods, the decision-maker is to choose only one, that is, the most convenient solution. The evaluation of the risk and uncertainty decisions in the process of knowledge and analysis of the current situation is achieved by a multitude of methods, the means that make it possible to identify, scienti cally determine the economic and nancial activity. The method of mathematical or modeling models, the signi cance of which is described and applied in the analysis and evaluation of scienti c research, which does not constitute a new discovery but which reproduces certain parts of the studied objectives in order to facilitate its scienti c research. Today it is impossible to conceive of an economic or nancial discipline that does not use in its process of knowledge methods of quantization, numerical expression, law, interdependence, measuring trends in the decision-making process. It is characteristic that even microeconomics in the theory of its generalization, in the deduction of a theory of maximal genericity, in its analyzes, often abstracts, uses statistical-mathematical methods, the elaboration of economic-mathematical models, the numerical, rigorous expression of some Processes And phenomena. Moreover, speci c economic disciplines are obliged to resort to this modern care tool, guaranteeing not only the precision of formulating the conclusions, but also the e ectiveness of the decisions on which, on this basis, they are based on an economic reality.