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Abstract
The aim of this paper is to set-up the algorithm for determining the degree of workability
of 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 algorithms
and based on the accurate information of the cultivation conditions, would result in the appropriate
use of time and capacity of the agricultural machines. In some sectors, such as agriculture or certain
industries, chance that certain event occurs plays a very important role. The influence of random
events, however, can be significantly reduced if decision makers are counting on them, reveal their
nature and gather as much information about them as possible. Justification of new testing methods
applied in the economy follows from the fact that, according to economic policy, the growing
burden 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. Treating
uncertain, vague and linguistically described phenomena and situations is facing difficulties in
classical mathematics. In fact, a large degree of uncertainty is primarily resulting from uncertain
external events. Fuzzy mathematical modeling can satisfactorily treat those parameters that are
uncertain, vague and subjectively evaluated. The algorithm of risk assessment should be based on
the opinion of economic experts, on the experience of the makers of planned decisions and on all
the 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 almost
exclusive 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 is
possible to develop a prototype of an expert system. Modeling problems in which the
interdependence 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.