INTELLECTUALIZATION OF AGROTECHNOLOGIES MANAGEMEN

Abstract

The agricultural industry is one of the most important areas of digitalization of the economy. At the same time, the content basis of digitalization is the technology of precision farming (TZ), which implements the tasks of agrotechnology management. These tasks are divided into two main groups according to the type of executive control system. The first group includes organizational management tasks, embodied in control decision-making systems (DSS) and implemented by management at various levels. The second group includes the tasks of managing field agricultural technologies, embodied in automated control systems (ASUAT). These tasks are implemented by automated and robotic technological machines. The effectiveness of management systems depends on the degree of human participation in the management process, i.e. on the level of his intellectualization. The high level of intellectualization depends on how widely the achievements of modern management science are involved in the creation of control systems. Such achievements are most fully used in analytical systems DSS and ASUAT. However, their actual use is faced with the lack of the required qualifications of rural producers. This problem can be solved by moving to expert control systems that do not require complex multi-step calculations. At the same time, the breakthrough level of such systems can be provided by cloud-based information systems, when knowledge bases (BRs) in expert systems will be formed in information processing centers and transmitted through the public cloud to local DSS and MISS. In order to make optimal decisions on KBs in local DSS and ASUAT, pattern recognition algorithms or special decision-making models can be used, the parameters of which are estimated by the KB, considered as a training sample.