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A Neural Network Analysis of the Fixed Capital Investment Trends in Regions of the Russian Federation

Kuznetsov Yu.A. National Research Lobachevsky State University of Nizhny Novgorod, Nizhny Novgorod, Russian Federation ( Kuznetsov_YuA@iee.unn.ru )

Perova V.I. National Research Lobachevsky State University of Nizhny Novgorod, Nizhny Novgorod, Russian Federation ( perova_vi@mail.ru )

Lastochkina E.I. National Research Lobachevsky State University of Nizhny Novgorod, Nizhny Novgorod, Russian Federation ( mmep@iee.unn.ru )

Journal: Digest Finance, #3, 2017

Importance The article considers the changes in and characteristics of the investment activities and behavior of the Russian Federation regions.
Objectives The article aims to analyze and describe the trends and characteristics of fixed capital investment behavior of the Russian Federation regions to ensure the economic growth and socio-economic development of the country and regions.
Methods We examine the regions' investment activities for the period from 2012 through 2014 using the neural modeling methodology on the basis of thirteen indicators characterizing the investment activities of the regions and defining their socio-economic development prospects. We also apply the Self Organizing Map using the STATISTICA software. Data of the Federal State Statistics Service of Russia on fixed investment by type of economic activity in the regions underlie our study.
Results The paper shows certain characteristics and peculiarities of the investment performance and behavior of the Russian Federation regions.
Conclusions and Relevance The cluster analysis of the Russian Federation regions' investment activities shows their uneven nature. The findings indicate the need for comprehensive measures to help change the structure of the investments involved and stimulate investment activity in all regions of the Russian Federation.


A neural network analysis of the fixed capital investment behavior of regions of the Russian Federation

Kuznetsov Yu.A. National Research Lobachevsky State University of Nizhny Novgorod, Nizhny Novgorod, Russian Federation ( Kuznetsov_YuA@iee.unn.ru )

Perova V.I. National Research Lobachevsky State University of Nizhny Novgorod, Nizhny Novgorod, Russian Federation ( perova_vi@mail.ru )

Lastochkina E.I. National Research Lobachevsky State University of Nizhny Novgorod, Nizhny Novgorod, Russian Federation ( mmep@iee.unn.ru )

Journal: Regional Economics: Theory and Pactice, #7, 2017

Subject The article considers the changes in and characteristics of the investment activities and behavior of the Russian Federation regions.
Objectives The article aims to analyze and describe the trends and characteristics of fixed capital investment behavior of the Russian Federation regions to ensure the economic growth and socio-economic development of the country and regions.
Methods We examine the regions' investment activities for the period from 2012 through 2014 using the neural modeling methodology on the basis of thirteen indicators characterizing the investment activities of the regions and defining their socio-economic development prospects. We also apply the Self Organizing Map using the STATISTICA software. Data of the Federal State Statistics Service of Russia on fixed investment by type of economic activity in the regions is the basis of our study.
Results The paper shows certain characteristics and peculiarities of the investment performance and behavior of the Russian Federation regions.
Conclusions The cluster analysis of the Russian Federation regions' investment activities shows their uneven nature. The results obtained indicate the need for comprehensive measures to help change the structure of the investments involved and stimulate investment activity in all regions of the Russian Federation.


Social and economic development of the Syrian Arab Republic during the pre-crisis period: A retrospective analysis

Kuznetsov Yu.A. National Research Lobachevsky State University of Nizhny Novgorod, Nizhny Novgorod, Russian Federation ( Kuznetsov_YuA@iee.unn.ru )

Perova V.I. National Research Lobachevsky State University of Nizhny Novgorod, Nizhny Novgorod, Russian Federation ( perova_vi@mail.ru )

Waddah Al Jarad. c National Research Lobachevsky State University of Nizhny Novgorod, Nizhny Novgorod, Russian Federation ( waddah.ja@gmail.com )

Journal: Economic Analysis: Theory and Practice, #7, 2017

Subject The article reviews the specifics of economic development of the Syrian Arab Republic during the pre-crisis period.
Objectives The purpose of the study is to analyze and describe trends in the economic development of the Syrian Arab Republic to define its actual economic situation during the pre-crisis period and prospects for economic advancement and social progress of the entire country and its certain provinces subject to peaceful development.
Methods We employ neural simulation based on indicators characterizing the economic condition of the country as a whole and its certain provinces. The research tools include self-organizing maps based on Deductor analytical platform.
Results The paper reveals major trends in GDP, focuses on economic restructuring of the Syrian Arab Republic. Based on five indicators of economic activity of provinces in the private sector, we performed a cluster analysis of their development. It shows that in 2007–2010, fourteen provinces were divided into three groups (clusters). We describe the composition and characteristics of each cluster, show changes in indicators of province development by clusters. The forecast for 2011–2017 is quite optimistic as long as peace is maintained.
Conclusions and Relevance The revealed specific features of socio-economic status of the Syrian Arab Republic before 2011 are indicative of unrealized opportunities for the country's economy since then.


Neural networks modeling in the activity analysis of the largest companies of Russian Federation

Kuznetsov Yu.A. doctor of physical-mathematical sciences, профессор, professor, head of chair the mathematical modeling of economic systems, Nizhny Novgorod state university N.I. Lobachevsky ( Yu-Kuzn@mm.unn.ru )

Perova V.I. candidate of physical-mathematical sciences, associate professor of chair the mathematical modeling of economic systems, Nizhny Novgorod state university N.I. Lobachevsky ( mmes@mm.unn.ru )

Journal: Economic Analysis: Theory and Practice, #31, 2010

The results of Neural Networks modeling of activity of 400 largest companies of the Russian Federation during 2005-2008 years are presented. The basis for researches is the annual rating of the largest companies of Russia on volume of realization of production, published in journal “Expert”. The main tools of researches - self-organizing Kohonen maps in package Viscovery SOMine. The analysis of self-organizing Kohonen maps has allowed to determine dynamics of development of various branches of economy and to reveal branches which companies possess prospects of growth.


Neuronetwork modeling of dynamics of innovative development of the regions of the Russian Federation

Kuznetsov Yu.A. Doctor of Physical and Mathematical Sciences, Professor, Head of the Department of Mathematical Modeling of Economic Systems, the Nizhny Novgorod State University named after N.I. Lobachevsky ( Yu-Kuzn@mm.unn.ru )

Perova V.I. Candidate of Physical and Mathematical Sciences, Associate Professor of Mathematical Modeling of Economic Systems, the Nizhny Novgorod State University named after N.I. Lobachevsky ( mmes@mm.unn.ru )

Journal: Regional Economics: Theory and Pactice, #4, 2014

The article is devoted to research of the features of innovative development of the regions of Russia. The carried-out analysis allowed to define dynamics of innovative activity of subjects of the Russian Federation and to reveal the regions possessing the greatest innovative activity. The instrument of researches in work are Kokhonen's realized in a Statistica package the self-organizing cards.


Some aspects of digital inequality rating of the RF regions

Kuznetsov Yu.A. Lobachevsky State University of Nizhny Novgorod - National Research University, Nizhny Novgorod, Russian Federation ( Yu-Kuzn@mm.unn.ru )

Markova S.E. Lobachevsky State University of Nizhny Novgorod - National Research University, Nizhny Novgorod, Russian Federation ( Svech@mail.ru )

Journal: Economic Analysis: Theory and Practice, #32, 2014

The article deals with some aspects of the development of information and communication technologies (ICT) in the Russian Federation. The authors state that the development of ICT has a positive effect on economic growth, human capital formation, productivity growth, the development of e-commerce, distance education, medicine, cultural exchange, etc. At the same time, the actual data on the penetration of cellular communication and the number of Internet users show a significant disparity in access to ICT and the Internet, leading, ultimately, to a digital divide. This digital divide may gradually turn into economic and social inequality. On the other hand, the free use of information and communication technology is becoming a driver of growth and professionalization what, in the end, means improving the competitiveness of selected industries and the national economy as a whole with the growth of information culture (digitization) of the working population. In Russia, the problem of digital divide of territories is particularly acute due to several features of the country (the length of the territory, socio-economic, demographic, climatic differences between regions, etc), so that the task of its elimination is a priority. Therefore, there is considerable interest in the analysis of the levels of information resources accessibility and information technology in the regions of Russia, as well as the ways to make better use of telecommunications technology. Analysis of statistical data regarding the current level and the dynamics of the digital divide, as well as a description of some of the qualitative features of the local (regional) markets of information and communication technologies have revealed the presence of differently directed dynamics of the digital divide at the federal level and at the level of the Federal districts. The authors are suggesting a number of measures, as a result of which it is possible to reduce the digital divide in the Russian Federation.


Economic and mathematical modeling of dynamics of change of generations of telecommunications services

Kuznetsov Yu.A. Lobachevsky State University of Nizhny Novgorod - National Research University, Nizhny Novgorod, Russian Federation ( Yu-Kuzn@mm.unn.ru )

Markova S.E. Lobachevsky State University of Nizhny Novgorod - National Research University, Nizhny Novgorod, Russian Federation ( mmes@mm.unn.ru )

Michasova O.V. Lobachevsky State University of Nizhny Novgorod - National Research University, National Research University of Higher School of Economics, Nizhny Novgorod, Russian Federation ( michasova@mm.unn.ru )

Journal: Financial Analytics: Science and Experience, #34, 2014

The article points out that while predicting and analyzing the financial performance of an enterprise it is very important to understand and take into account the size of the market, the potential demand and the proximity of an industry to saturation. The paper proposes an approach within the framework of which we can define the carrying capacity of the market, subject to the existence of two technologies, one of which is gradually replacing another one. As the subject of the study,we have selected the dynamics of the market data transfer that is studied using the methods of economic-mathematical modeling of diffusion of innovation. The transition from the dial-up access to Internet to the broadband access takes place within the competitive interaction between two consecutive generations of technology, since it can be described by the mathematical Gilpin -Ayala model of dynamics of interaction of two biological populations. The objectives of the paper are to confirm the hypothesis that given model can be used to describe the process of change of technologies and the formation of the forecast on the prospects of the development of the broadband access to Internet. To determine the coefficients of the model, the authors built an econometric model, described by the system of simultaneous equations, as well as made the comparison of the Gilpin-Ayala model with the more popular and widely used Trays-Volterra model. The research has shown that Gilpin-Ayala model better describes the process of diffusion of innovations of the data transfer market. In addition, the quality of the resulting prediction was rather high. The authors emphasize that as the result of the simulation it was found that the market for broadband distribution is close to saturation, so in order to ensure the sustainable financial performance of the service-providers, the search of new directions of activity, in particular, the promotion of mobile Internet technologies come to the fore.


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