Scientific Journal of KubSAU

The overall performance of the company is largely determined by the efficiency of production processes carried out by them. In this sense, the model estimation of efficiency is one of working out in detail of the model of the production process. Accuracy, flexibility and sensitivity of the valuation models depend strongly on the completeness of the accounting features of the production model. In the literature, examine various approaches to the assessment of economic efficiency of production processes. Many of them are characterized by localizing assessment in relation to specific industries or areas of industrial activity. The disadvantage of such approaches is their poor tolerance to the valuation model in other local areas, such as agriculture. To overcome this problem, we propose to carry out the differentiation of the components of the production process, based on the classical approach, but allowing to take into account the distinctive characteristics of agricultural production. For agricultural enterprises are defined the characteristics of the production process. The authors proposed a generalized model that allows assessing the efficiency of production processes in various areas of industrial activity. In the proposed model there are shown superimposed on the manufacturing process constraints. To ensure the continuity of an estimation of efficiency of production processes into the model we have introduced components that transform the characteristics of a production subsystem into the characteristics of the economic subsystem

In the context of the objective existence of risk and economic, human and other losses related with it, there is a need in a specific mechanism, which would allow the best way to predict the damage caused by the emergency. These risk management tools in emergency situations are monitoring and forecasting. In this research work, time series are used as a signal; they contain information about the number of fires in the Karachayevo-Cherkessia in the period of 1983- 2014. In solving the problem, the authors applied wavelet tools for data cleaning from noise, anomalies that have provided quality model building reliable forecast - possible number of fires in one quarter ahead. This example shows that for the construction of this forecast there is no need for a rigorous mathematical model specification, which is especially valuable in the analysis of poorly formalized processes. We have noted that most of the tasks in emergencies fall into this category of processes

This article describes the opportunities and prospects for the deployment of decision support system for the adequacy of the level of lending to small agricultural enterprises in the cloud environment. It reveals the shortcomings in the existing automation of small businesses, and therefore the necessity of developing a system to enable managers to quickly and correctly calculate the amount of required loan funds. The developed system has the ability to work remotely due to the lack of binding the user to a specific personal computer. It is implemented through the development of a DSS using cloud computing, in which computer resources are provided to the Internet users in the form of "online service". The article describes the architecture of popular models and cloud Webapplications; after that, it was concluded to use the Saas model with Multi-Tenant-mode support in the model development. The study provides an overview of the DSS functioning in the cloud. It has noted the main features of the software implementation of the system relating to the use of cloud technologies. We have calculated the cost of placing an application in the cloud via the online cost calculator called Microsoft Azure. We have also performed a preliminary assessment of the payback period of the project implementation of DSS. It is concluded, that this technology would be competitive at the software market

The article presents the architecture of decision support system for the adequacy of the level of lending to small agricultural companies, which implements in its functionality the complex of models: the optimization of selling price of products, the efficiency mark for using of credit funds of single-product and multi-product companies by determined and fuzzy methods, assessment of the system stability of the enterprise. The system has the ability to work remotely using cloud computing, in which computing resources provided by the Internet users in the form of "online service". The article substantiates the need for the development of decision support systems for the adequacy of the level of lending to small agricultural enterprises. We have compiled requirements for the development of an appropriate system and identified a set of models to be implemented in the DSS , described the relationship between them and the technique of working with them. We have also defined names of the input and output data at various stages of working with the DSS as well as the generalized algorithm of the system. Based on the above, the article proposes and describes the architecture of decision support system. It is concluded, that the DSS is an interactive automated system that uses a model of decision-making, providing users with efficient access to data and provides them with a variety of opportunities to display information