Application of Fuzzy Sets within Measuring and Managing certain Agricultural Risks

The aim of this paper is to set-up the algorithm for determining the degree of workabilityof the soil, to help the owners of family farms to plan working hours of agricultural machines, i.e.with the machine park management. The plans, which would be made by use of these algorithmsand based on the accurate information of the cultivation conditions, would result in the appropriateuse of time and capacity of the agricultural machines. In some sectors, such as agriculture or certainindustries, chance that certain event occurs plays a very important role. The influence of randomevents, however, can be significantly reduced if decision makers are counting on them, reveal theirnature and gather as much information about them as possible. Justification of new testing methodsapplied in the economy follows from the fact that, according to economic policy, the growingburden of risk that comes from the uncertainty is borne by farmers.The method that was used in the study is based on the Fuzzy mathematical modeling. Treatinguncertain, vague and linguistically described phenomena and situations is facing difficulties inclassical mathematics. In fact, a large degree of uncertainty is primarily resulting from uncertainexternal events. Fuzzy mathematical modeling can satisfactorily treat those parameters that areuncertain, vague and subjectively evaluated. The algorithm of risk assessment should be based onthe opinion of economic experts, on the experience of the makers of planned decisions and on allthe available data. Solving this problem can be approached in three ways: a) conventional method,b) applying the expert system, c) applying the theory of fuzzy sets.The main characteristic of the traditional way of solving the problem of evaluation is the almostexclusive reliance on measurable economic effects (time and money). Only in some rare cases,additional criteria are taken into account. Because of the importance of additional criteria, it ispossible to develop a prototype of an expert system. Modeling problems in which theinterdependence between the variables is very complex, fuzzy logic can be successfully applied.The complete review and analysis of the problem relying only on knowledge, experience of experts,without the fuzzy logic, would be impossible.