Name
Kolosova Nataliya Sergeyevna
Scholastic degree
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Academic rank
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Honorary rank
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Organization, job position
Kuban State Technological University
Web site url
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Articles count: 2
This article analyzes the best practices of choosing the
optimal policy for replacement of vehicle fleet. The
problem of replacement equipment was revealed. For
each of these methods we gave objective function,
constraints. We have found the best method of optimal
plan of replacing the vehicle fleet in the company,
allowing us to obtain accurate, economically viable
new equipment purchase plan during a certain period.
We have selected a number of important factors that
influence the choice of payment method replacement
policy and built PivotTable methods and factors. The
selected as part of the research methodology will
significantly reduce the labor and time, which will lead
to an increase in productivity of the enterprise as a
whole. The article gives a practical justification for the
need to address the problem of choosing the optimal
policy of replacing the vehicle fleet
This study proposes a method of determining the cost
of 1 sq. m. apartment on the example of Krasnodar,
which is especially important in connection with the
necessity of reliable and valid assessment of the
property value in a modern market economy. We have
performed an analysis of data on apartments in
Krasnodar from the site of the Regional Energy
Commission - prices and tariffs department of the
Krasnodar region. We have also had an exploratory
analysis of available data on the subject of emissions
and insignificant data (by constructing line graphs and
scatter plots); we have also checked for possible
dependencies between observations and between
variables (built correlation matrix). We have selected
variables is linear, the regression model for the
variable "cost of 1 sq. m the total area, ths. rub.
"(multiple regression). Using regression analysis as a
method of mathematical statistics we have revealed a
form of analytical dependence of the result of the
predictor variables and the degree of this dependence