| Annotation: | Methods. The results are obtained through the use of methods: abstraction – in determining the nature of the category «risk»; analysis and synthesis – in highlighting the nature of the risks of agricultural enterprises; logical and historical – in the study of the evolution of approaches to determining the risks of agricultural enterprises; method of classifications – when summarizing the existing approaches to mathematical methods of risk assessment in groups; general and special - in establishing the unity of existing methods of risk assessment; comparison – to determine the advantages and disadvantages of the types of mathematical assessment of the magnitude of risks; abstract-logical analysis – to generalize and formulate conclusions. Results. It is established that against the background of a large number of definitions of risk in the scientific literature there is no established understanding of it. The essential features of agricultural production are analyzed and their influence on the formation of risks of agricultural enterprises is determined. The essential signs of risks of agricultural enterprises and their features are revealed. There is analyzed the essence of the main modern methods of risk assessment and modeling in relation to agro-industrial enterprises (deterministic method, statistical method, probabilistic-statistical method, theoretical-probabilistic method, logical-linguistic method, simulation method, expert method, especially fuzzy sets method). The advantages of using fuzzy logic methods to assess the risks of agricultural enterprises are shown. An algorithm for risk assessment based on the fuzzy logic method is presented. Novelty. On the basis of theoretical and analytical generalizations on mathematical methods of risk assessment of agricultural enterprises, there is substantiated the possibility of using the mathematical apparatus of fuzzy logic and logical-linguistic modeling to assess the source information, which has a fuzzy, uncertain and probabilistic nature. Practical value. The development of methods for identifying and describing sources of danger, as well as the conditions of their manifestation during the operation of these facilities is crucial to the development and implementation of measures to prevent risks on agricultural sites. The limitations of available scientific and methodological materials does not meet practical needs. Therefore, the use of logical-linguistic modeling to assess risks seems promising. This assessment of the presentation of fuzzy information is the most acceptable, as it allows to formalize the knowledge of experts in a convenient semantic form. |
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