The are crop planning problems exist in a modern agriculture of Ukraine. With the help of the intelligent support system for agro-technological decisions proposed by the authors, it is possible to simplify the planning process by using the concept of precision farming. Modern fields monitoring methods were analyzed and methods that will be used in the intelligent system are identified. The k-means method is one of them and will be applied to field clustering. The authors analyzed modern research and publications related to the concept of precision farming and the problem of implementing modern innovative information systems in agriculture of Ukraine. The decomposition of the intelligent system was carried out. Six main subsystems were identified, functional requirements were developed for each of them. Modern methods of fields monitoring are analyzed and methods that will be used in the intelligent system are identified, one of which is the k-means method, which will be applied to field clustering. Based on the already developed requirements, the authors have developed the general architecture of the system. The notation TOGAF was applied for the graphical display of the architecture. Based on the proposed architecture, intelligent system software was created. As a result of testing the soft-ware of the intelligent system, it is possible to draw a conclusion about its efficiency and readiness for implementation. The designed and developed system allows to carry out intellectual analysis of historical data of crops, to display results in the form of tables and graphs, to carry out planning of crops, agrotechnological operations and fertilizer application. The introduction of this system will improve the quality of management decisions and productivity of agricultural activities.
Extraction of ionosphere parameters in ionograms using deep learning
