Open AccessTHE ECONOMIC-MATHEMATICAL MODEL OF RISK ANALYSIS IN AGRICULTURE IN CONDITIONS OF UNCERTAINTY
Author(s) -
Ruslana Levkina,
Iryna Kravchuk,
Iryna Sakhno,
Kateryna Kramarenko,
Аліса Шевченко
Publication year - 2019
Publication title -
fìnansovo-kreditna dìâlʹnìstʹ: problemi teorìì̈ ta praktiki
Language(s) - English
Resource type - Journals
eISSN - 2310-8770
pISSN - 2306-4994
DOI - 10.18371/fcaptp.v3i30.179560
Subject(s) - computer science , task (project management) , risk analysis (engineering) , field (mathematics) , impossibility , statement (logic) , reliability (semiconductor) , problem statement , work (physics) , agriculture , operations research , data mining , management science , engineering , systems engineering , mathematics , medicine , mechanical engineering , ecology , power (physics) , physics , quantum mechanics , political science , law , pure mathematics , biology
The use of automatic information systems for risk analysis from other countries in Ukraine is extremely difficult due to the lack of databases on factors affecting risk, not only at the regional but also at the state level. Therefore, it became necessary to create an economic-mathematical model for information processing, including incomplete data, on factors affecting risks for use in the agricultural sector of Ukraine. Such a model was formalized, created and tested.The developed economic-mathematical model of the risk analysis system presupposes the necessity of preliminary statement of the task by an expert in the field of agriculture and further automatic work of the software complex adapted to the conditions of use by specialists in economic and mathematical modeling.Because of there are mostly no databases in Ukraine on factors affecting risks, it is needful to evaluate and use incomplete data or data for limited time intervals.One of the components of the algorithm is the method of simulation. The automatic information system for risk analysis generates so-called pseudo-random sequences and gradually verifies the reliability of their description of each of the risks named by the expert, specific to this particular task for the farms. Such a method has already been tested on tasks whose solution was faced with a lack of statistical information, and the impossibility of using analytical methods.Reducing the execution time of the task is facilitated by the formation of a library of working arrays, which accumulates during the operation of an automatic risk analysis system.Reducing the time of the task is facilitated by the formation of library tool working arrays, which accumulates during the operation of the automatic risk analysis system.To simplify the processing of incoming information and work out calculations, it is suggested to use a parametric model.This method was borrowed from the experience of using gert-networks.To test the effectiveness of the developed algorithm, a risk calculation has been made for farms that grow cereals, legumes and sunflowers. The results of the calculation showed reliable values of risk factors.It was determined which of the risks is more significant for the producers of these agricultural products.