Fuzzy modelling for tasks of management of the agricultural-industrial complex
| Autor: | K. V. Evdokimov, Yu. V. Amagaeva, V. E. Parfenova, G. G. Bulgakova |
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| Rok vydání: | 2019 |
| Předmět: | |
| Zdroj: | IOP Conference Series: Materials Science and Engineering. 666:012067 |
| ISSN: | 1757-899X 1757-8981 |
| Popis: | The problem of modeling and accounting for uncertainty in modern tasks of management is relevant. The effectiveness of the decisions depends significantly on the methods for describing the uncertainty in the problem. The greatest development in agrarian science received optimization and econometric models. How-ever, these models are based on quantitative determined initial information and accounting for uncertainty as randomness, which is described by probabilistic and statistical methods. Meanwhile, many modern decision-making tasks in planning and managing agricultural production are characterized by the presence of uncertain factors, as well as the availability of high-quality, inaccurate or in-complete information. To account and describe such uncertainty, an alternative approach to the probabilistic approach is needed. Fuzzy set theory is one of the most effective mathematical tools aimed at formalizing and processing uncertain information. The econometrics section related to using fuzzy set theory in regression analysis is developing methods of fuzzy regression modeling. The possibilities of using fuzzy regression modeling tools for analyzing management processes of agricultural production are discussed in this article. |
| Databáze: | OpenAIRE |
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