Innovation model of agricultural technologies based on intuitionistic fuzzy sets

Abstract

The selection and rational use of mechanization significantly affects the cost of agricultural products. To achieve the best financial effects, it is necessary to optimize the use of existing machine parks. The authors suggest a decision tree for deciding whether to 'innovate or not'. The aim of the research is to define an algorithm that determines whether or not the land is arable, and in this way to help the owner of the family farm in the planning of working hours for agricultural machines, i.e., managing the machine park. The lack of plans, which stems from the lack of accurate data on the appropriate conditions of cultivation, leads to inappropriate use of time and the capacity of the machine park. The decision process is split into four compound variables: biological conditions, economic environment, technological conditions, and expertise and workmanship quality. Linguistic values of these variables are modeled with intuitionistic fuzzy sets, allowing for imprecision in data as well as experts' hesitation.