Name
Saykinov Viktor Evgenievich
Scholastic degree
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Academic rank
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Honorary rank
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Organization, job position
Kuban State Agrarian University
Web site url
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Articles count: 4
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
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
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
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