Economic growth rate management by soft computing approach

Goran Maksimović, Srđan Jović and Radomir Jovanović

Physica A: Statistical Mechanics and its Applications, 2017, vol. 465, issue C, 520-524

Abstract: Economic growth rate management is very important process in order to improve the economic stability of any country. The main goal of the study was to manage the impact of agriculture, manufacturing, industry and services on the economic growth rate prediction. Soft computing methodology was used in order to select the inputs influence on the economic growth rate prediction. It is known that the economic growth may be developed on the basis of combination of different factors. Gross domestic product (GDP) was used as economic growth indicator. It was found services have the highest impact on the GDP growth rate. On the contrary, the manufacturing has the smallest impact on the GDP growth rate.

Keywords: Neuro-fuzzy; Forecasting; Economic growth; GDP (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0378437116305878
Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:465:y:2017:i:c:p:520-524

DOI: 10.1016/j.physa.2016.08.063

Access Statistics for this article

Physica A: Statistical Mechanics and its Applications is currently edited by K. A. Dawson, J. O. Indekeu, H.E. Stanley and C. Tsallis

More articles in Physica A: Statistical Mechanics and its Applications from Elsevier
Bibliographic data for series maintained by Catherine Liu ().