Intelligent decision support in the optimization of irrigation systems in agriculture

The issues of determining the optimal values regulatory parameters irrigation systems engaged in cultivation agricultural crops are considered. Following requirements a market economy, main emphasis is placed on taking into account two types criteria: maximizing yield and minimizing monetary costs. proposed method for solving multi-criteria optimization problem based combination minimax criterion medium-step convolution, which makes it possible to scalarize vector optimality with access smooth methods. Concerning case priority uncertainty according particular criteria, an intelligent algorithm approximation preference function decision-maker by fuzzy Mamdani model. system used growing cotton results differ favorably from average values. one hectare republic- increased 2%, costs - reduced 4.5%. It could be concluded that developed methodology bypass computational difficulties arise when problems obtain real conditions certainty goals.