Methodological management tools of irrigation with artificial intelligence

Purpose: to develop the concept of irrigation management systems using integrated artificial intelligence technologies. Materials and methods. The working hypothesis research was assumption priority cluster application technologies in solving urgent problems management. At same time, basis information-computing unit control system should be deterministic algorithms proven solutions. Results. Within framework proposed concept, a neural network can used as for problem, or it only adapt parameters models used. impact points traditional, - analytical are determined by need parameters, fine-tune coefficients methodological tools scope is quite wide. Artificial solve planning operational management, image recognition satellite monitoring soil moisture, interpolation moisture data area, forecasting profile. An algorithm improve reliability total water consumption irrigated crops regional landscape aspect developed research. allows self-learn refine values bioclimatic coefficients, with respect cumulative influence local factors. Conclusions: has been new scientific approaches have effectively problem adapting at level an field, even taking into account intra-field variability.