THE PROPORTIONS AND RATES OF ECONOMIC ACTIVITIES AS A FACTOR OF GROSS VALUE ADDED MAXIMIZATION IN TRANSITION ECONOMY

Authors

  • Yaroslav I. VYKLYUK
  • Valeriy K. YEVDOKYMENKO
  • Ihor V. YASKAL

DOI:

https://doi.org/10.1515/saeb-2016-0104

Keywords:

gross value added, structure of economic activities, Hopfield’s network, strategy

Abstract

Sustain growth of value added is one of the most important problem in many countries with transition economy. The article provides new evidence about determining the future dynamics of the economic activities with increasing value added. In this paper, we have used Hopfield’s neural network to clarify the strategies of social and economic development of country. Three types of strategies have been created with using mathematical models and quantitative assessment of their efficiency has been made. From the simulation results, it is observed that state regulation based on this methodology can build the basis for further improvements in economic policy.

JEL Codes - O21, C45, P24

References

Akbari, R., and Ziarati, K., 2011. A multi level evolutionary algorithm for optimizing numerical functions. International Journal of Industrial Engineering Computations, 2, 419-430. doi: http://dx.doi.org/10.5267/j.ijiec.2010.03.002

Atencia, M., Joya, G., and Sandoval, F., 2005. Hopfield Neural Networks for Parametric Identification of Dynamical Systems. Neural Processing Letters, 21(2), 143-152. doi: http://dx.doi.org/10.1007/s11063-004-3424-3

Balakrishnan, S., Kannan, P. S., Aravindan, C., and Subathra, P., 2003. On-line emission and economic load dispatch using adaptive Hopfield neural network. Applied Soft Computing, 2(4), 297-305. doi: http://dx.doi.org/10.1016/S1568-4946(02)00062-5

Cohen, M. A., and Grossberg, S., 1983. Absolute stability of global pattern formation and parallel memory storage by competitive neural networks. IEEE Transactions on Systems, Man, and Cybernetics, 13(5), 815-826. doi: http://dx.doi.org/10.1109/TSMC.1983.6313075

Dachin, A., and Burcea, F. C., 2013. Structural changes and productivity in the crisis period in Romania. The industry case. Theoretical and Applied Economics, XX(6(583)), 139-148.

Garg, E. M., Singh, E. M., and Girdher, E. V., 2012. Comparative study of economic load dispatch (ELD) using modified Hopfield neural network. International Journal of Computing & Business Research. http://www.researchmanuscripts.com/isociety2012/43.pdf

Gedz, M., 2014. Regulation of Structural Changes in the economy of Ukraine. The Russian Academic Journal, 29(3), 35-38. doi: http://dx.doi.org/10.15535/279

Hopfield, J. J., 1982. Neural Networks and Physical Systems with Emergent Collective Computational Abilities. Proceedings of the National Academy of Sciences of the United States of America, 79(8), 2554-2558. doi: http://dx.doi.org/10.1073/pnas.79.8.2554

Katsikatsou, M., Moustaki, I., Yang-Wallentin, F., and Jöreskog, K. G., 2012. Pairwise likelihood estimation for factor analysis models with ordinal data. Computational Statistics & Data Analysis, 56(12), 4243-4258. doi: http://dx.doi.org/10.1016/j.csda.2012.04.010

Labaye, E., Sjåtil, P. E., Bogdan, W., Novak, J., Mischke, J., Fruk, M., and Ionuțiu, O., 2013. A new dawn: Reigniting growth in Central and Eastern Europe Retrieved from http://www.mckinsey.com/insights/economic_studies/a_new_dawn_reigniting_growth_in_central_and_eastern_europe

Lee, K. Y., Sode-Yome, A., and Park, J. H., 1998. Adaptive Hopfield neural networks for economic load dispatch. IEEE Transactions on Power Systems, 13(2), 519-526. doi: http://dx.doi.org/10.1109/59.667377

Maksimov, Y. A., and Filipovskaya, E. A., 1982. Algorithms for solving nonlinear programming problems. Moscow: MIFI.

Mishra, S. K., and Mishra, S. K., 2015. A Comparative Study of Solution of Economic Load Dispatch Problem in Power Systems in the Environmental Perspective. Procedia Computer Science, 48, 96-100. doi: http://dx.doi.org/10.1016/j.procs.2015.04.156

Moor, J. H., and Weatherford, L. R., 2004. Decision modelling with Microsoft Excel (6 ed.). Moscow: Williams Publishing House.

Pavelescu, F., 2012. Fluctuation of economic activity, sectoral distribution of gross value added and the size of backward multipliers in Romania during the period 1989-2009. Romanian Journal of Economics, 35(2(44)), 88-112.

Pyrog, O. V., 2014. Structural changes in the model of national economy of Ukraine under an influence of informatization of society. Effective Economy, (7). http://www.economy.nayka.com.ua/?op=1&z=3170

Russu, C., 2015. Structural Changes Produced in the Romanian Manufacturing Industry in the Last Two Decades. Procedia Economics and Finance, 22, 323-332. doi: http://dx.doi.org/10.1016/S2212-5671(15)00296-8

Skribane, I., and Jekabsone, S., 2013. Structural changes in the economy of Latvia after it joined the European Union. Intellectual Economics, 7(1(15)), 29-41.

Vyklyuk, Y., Rotar, A., and Yevdokymenko, V., 2013. Formation of strategy reproduction patterns of economic activity in the regions based Soft Computing in the context of accelerating the growth of the gross regional product. Collection Of Scientific Articles, Economic Sciences, 9, 99-116.

Vyklyuk, Y., and Yevdokymenko, V., 2013. Development of Soft Computing techniques to optimize the formation of strategy reproduction patterns of economic activity in the regions. Paper presented at the International Scientific Conference Information technology, economics and law. State and Development Trends, Chernivtsi.

Vyklyuk, Y., and Yevdokymenko, V., 2014. New methods of Soft Computing in regional development strategy formation. MEST Journal, 2(2), 274-284. doi: http://dx.doi.org/10.12709/mest.02.02.02.28

Wan-Liang, W., Xin-Li, X., and Qi-Di, W., 2003. Hopfield neural networks approach for job shop scheduling problems. Paper presented at the IEEE International Symposium on Intelligent Control, Houston, Texas.

Yevdokymenko, V., 2013. Features of reproduction governance of social and economic processes of the region in modern conditions. Chernivtsi: Tekhnodruk.

Zhang, J., Chung, H. S. H., and Lo, W. L., 2007. Clustering-Based Adaptive Crossover and Mutation Probabilities for Genetic Algorithms. IEEE Transactions on Evolutionary Computation, 11(3), 326-335. doi: http://dx.doi.org/10.1109/TEVC.2006.880727

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Published

2016-03-03

How to Cite

VYKLYUK, Y. I., YEVDOKYMENKO, V. K., & YASKAL, I. V. (2016). THE PROPORTIONS AND RATES OF ECONOMIC ACTIVITIES AS A FACTOR OF GROSS VALUE ADDED MAXIMIZATION IN TRANSITION ECONOMY. Scientific Annals of Economics and Business, 63(1), 55–64. https://doi.org/10.1515/saeb-2016-0104

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