Scientific Journal of KubSAU

Grain is the strategic importance and is the basis for food security. The gross national product share of grain and its products is about 10-15%. It always stands out from other types of raw materials, as used to produce the most massive daily foods. When selecting cultivation technology agricultural crop agronomist has at its disposal a database of more than a hundred times-personal of alternative technologies for each crop. Prior to the decision-maker (DMP) is the task of specific criteria to select the most suitable for the owners, climatic zone of technology cultivating culture. These circumstances explain the relevance of in-depth research of economic and mathematical models and methods of analysis and evaluation of the economic efficiency of technologies of cultivation agricultural crops. The possibility of developing a set of mathematical models and methods for multi-criteria analysis and assessment key technologies of cultivation of agricultural crops

Production and processing of grains formed in the national economic system of the country a number of cereals-governmental sectors, such as grain production, grain elevator industry, flour, cereals and mixed fodder production, which constitute the grain complex country. The significance and role of the grain as a commodity in the state economy can not be overestimated. This product, is totally liquid, which has a constant, steady demand at any time of the year, in any region. Ongoing measures to increase grain production and improve its implementation did not have a complex character, therefore, insignificant effect on the efficiency of the industry and the competitiveness of grain production. The shortagecovered by imports.According to the characteristics of management in agriculture, it should be emphasized that the absence of objective and timely information at all stages of production of the plant-breeding, and as a result, non-optimal choice of technology of cultivation of agricultural crops, might result in the fact that the cost of labor and material resources increases significantly, the company does not receive profits, and sometimes suffers losses. When selecting cultivation technology for agricultural crops, an agronomist has a database of more than a hundred times-personal of alternative technologies for each crop. It is up to the decision-maker (DMP) to find specific criteria to select the most suitable (for the owners and the climatic zone) technology of cultivating for the culture. These circumstances explain the relevance of in-depth research of economic and mathematical models and methods of analysis and evaluation of the economic efficiency of technologies of cultivation agricultural crops. The article deals with the process of developing multicriteria economic-mathematical model of a comprehensive assessment of technology of cultivation of agricultural crops.

Plant growing successes influence the effectiveness not only the branch in itself, but the other agricultural branches and economics of agricultural enterprises in general. In the article the method of calculation of sufficient balance soil is considered.

Plant growing successes influence the effectiveness of not only the branch in itself, but of the other agricultural branches and economics of agricultural enterprises in general as well. Models and methods of decision taking process improvement in plant growing were considered in the article.

Car license plates recognition problem is one of the typical tasks of computer vision. Video surveillance software usually provides license plates recognition function. Meanwhile, there are many approaches to solve this problem, where template-based methods are the most common. Such methods providing predictable and short enough execution time, and little percent of mistakes. However, such methods are far less effective in case there is a need to recognize car’s license plate, which may be located in unpredictable place, typed in undefined font and on non-standard background, or without strict formatting. For example, USA car license plates. One of the methods to increase effectiveness and quality of such license plates recognition is to use neural networks. It is assumed, that neural networks usage can significantly increase recognition quality. Nevertheless, neural networks usage entails difficulties of it’s training, and often becomes less efficient as template-based methods usage. This article discusses probability of usage of convolutional neural network, which was trained using MNIST (Mixed National Institute of Standards and Technology) database. This article is a review of usage of templates and neural networks for car’s license plate recognition in terms of quality, performance and complexity of the usage