Study of Economic Systems Using the Simulation-Based Statistical Modeling Method

Batkovskiy, Aleksandr Mikhaylovich; Коновалова, А. В.; Семенова, Е. Г.; Trofimets, V. Ya.; Фомина, А. В.

doi:10.5901/mjss.2015.v6n4s4p369

Cited by 5 publications

(5 citation statements)

References 17 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In terms of a transition from the centralized distribution approach, it is important to maintain sustainabille operation of the enterprise. Researchers approach these tasks with the help of simulation techniques (Batkovskiy et al, 2015).…”

Section: Methodsmentioning

confidence: 99%

Sustainability in Local Power Supply Systems of Production Facilities Where There Is the Compensatory Use of Renewable Energy Sources

Todorov¹,

Vlasov

Volkova

et al. 2020

IJEEP

View full text Add to dashboard Cite

Renewable energy has become a promising way to meet growing energy needs in the society. However, operation of power supply systems based on renewable energy sources (RES) depends on a number of uncontrolled factors. This imposes certain restrictions on applications and causes applicationrelated challenges. At this point, the search for the best combination of applied energy sources has been still a key issue. Methodological approaches to the solution to this problem are diverse. The idea of our research is the application of tools from economics and mathematics to measure the best mutual substitution of energy resources in the production facility local power supply system. Authors have considered the possible application of RES through the example of the Russian-based production facility typical in terms of average power consumption and size. Authors chose a solar power plant as a RES. From the simulation results, authors conclude that when using RES, in terms of gross figures, there is about 20-25% less consumption. This makes it possible to achieve the balanced energy consumption from traditional sources throughout a production cycle. Our calculations have showed that, depending on the seasonal prevalence, it is possible to reduce average daily costs for power (in case of compensation from RES) by about 15.75% in the first season, 37.04% in the second season, and 25.44% in the third season. As for time period, in the second season, in the half-peak period (43.68%), we achieve the highest saving, while the lowest saving in the half-peak period of the first season (1.22%). Thus, the application of the solar power plant as a part of the local power supply system of the production facility makes it possible on average to achieve the 13% less energy consumed from centralized sources. It is safe to say that the application of combined sources of power in local power supply systems of production facilities is economically feasible to compensate for peak and half-peak loads. Authors have concluded that the potential of RES at the enterprise might be only developed as that of an additional energy resource and full substitution is impossible.

show abstract

Section: Methodsmentioning

confidence: 99%

Sustainability in Local Power Supply Systems of Production Facilities Where There Is the Compensatory Use of Renewable Energy Sources

Todorov¹,

Vlasov

Volkova

et al. 2020

IJEEP

View full text Add to dashboard Cite

show abstract

“…Mechanisms of control and modelling of the production process and goods consumption is an important objective of the economic strategy (Batkovskiy et al, 2015). One of the important areas in the study of economic processes is the study of the economic agents' behaviour in the neighbourhood of the equilibrium point.…”

Section: Production Model Of Pricing Based On Hysteretic Factorsmentioning

confidence: 99%

Dynamic Model of Optimal Production Control in a Hysteretic Behaviour of Economic Agents

Alexander¹,

Виктор²,

Olga³

et al. 2017

ERSJ

View full text Add to dashboard Cite

The hysteresis nature of demand, depending on the price ratio and purchasing power, is well-known, but mathematical models that describe this relationship have not been developed so far. This article provides a dynamic model of optimal production within price hysteretic behaviour. Unlike the standard description methods, the proposed cobweb model provides for qualitative description of the solution to the equation at the slowly changing control. The article also describes the production model enable to determine the adjustment dynamics of product quantity from the manufacturer and the consumer. The solution is described by standard methods of optimal control theory.

show abstract

“…Monte Carlo (MC) simulation is a well-known method of scientific analysis that includes a wide range of stochastic techniques used to quantitatively evaluate the behavior of complex systems or processes. This method has many applications in economics and finance, in general (e.g., [10][11][12][13][14]) and in GDP-related research, in particular (e.g., [15][16][17]). Conceptually, the structure of most MC experiments can be considered to include three components: a) generating input data to model uncertainty; b) randomly sampling through multiple repeatedruns (simulations) of systems' or processes' models (simulation logic); c) quantitatively evaluating the characteristics ofthe model outputs (e.g., [11,18,19]).…”

Section: Introductionmentioning

confidence: 99%

“…This method has many applications in economics and finance, in general (e.g., [10][11][12][13][14]) and in GDP-related research, in particular (e.g., [15][16][17]). Conceptually, the structure of most MC experiments can be considered to include three components: a) generating input data to model uncertainty; b) randomly sampling through multiple repeatedruns (simulations) of systems' or processes' models (simulation logic); c) quantitatively evaluating the characteristics ofthe model outputs (e.g., [11,18,19]). This note is focused on modelling input data for MC simulation.…”

Section: Introductionmentioning

confidence: 99%

Using Interpolation for Generating Input Data for the Gross Domestic Product Monte Carlo Simulation

Botchkarev

2023

Beneficium

View full text Add to dashboard Cite

Input modelling is a complex task within the Monte Carlo simulation, especially when the systems and processes under investigation reveal the non-linear behavior of several interdependent variables. Commonly used approaches for Monte Carlo simulation input modelling include selecting probability distributions and fitting them to existing data; resampling random variates from historical data; and using real-world data as an input model, which in the age of big data becomes more feasible. Each of the approaches comes with its own set of drawbacks. This note aims to describe a new method of input modelling for GDP Monte Carlo simulation based on interpolation of the GDP historical records. Also, this method has been implemented as a publicly available online tool using the Microsoft Azure Machine Learning Studio. A similar approach can be applied to other macroeconomic indicators, e.g., consumer price index (inflation) or current employment statistics. This note is intended for economists, data scientists, and operations research analysts interested in the GDP Monte Carlo simulation. It can also be used by academics, researchers, and practitioners in a broad subject area for generating input data for Monte Carlo simulation. Specifically, it can be of interest for Ph.D. candidates (VAC specialty 5.2.6) performing development of theory and methods of decision-making in economic and social systems, and application of artificial intelligence and big data methods in management.

show abstract

Study of Economic Systems Using the Simulation-Based Statistical Modeling Method

Abstract: This article analyzes theoretical and methodical aspects of study of economic systems using the simulation-based

Cited by 5 publications

References 17 publications

Sustainability in Local Power Supply Systems of Production Facilities Where There Is the Compensatory Use of Renewable Energy Sources

Sustainability in Local Power Supply Systems of Production Facilities Where There Is the Compensatory Use of Renewable Energy Sources

Dynamic Model of Optimal Production Control in a Hysteretic Behaviour of Economic Agents

Using Interpolation for Generating Input Data for the Gross Domestic Product Monte Carlo Simulation

Contact Info

Product

Resources

About