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Research Article

WORLD DEVELOPMENT INDICATORS ANALYTICS FOR SOUTH ASIAN ASSOCIATION FOR REGIONAL COOPERATION COUNTRIES

K
Kavita Pabreja Associate Professor and Head of Department of Computer Science, Maharaja Surajmal Institute, New Delhi, India
Volume 12, Issue 2 Pages 147-160 October 30, 2016 626 downloads
Article overview

Abstract

Data is an asset and offers tremendous opportunities for enabling innovation by observing previously unobserved patterns. Gross Domestic Product growth is considered as one of the most important parameters to understand the economical position of a nation. The economic health of a country depends upon many factors viz. consumption, business investment, government expenditure and net exports. In this study, an attempt has been made to perform analytics on education, health, environment and economic parameters of South Asian Association for Regional Cooperation countries. The datasets under study have been downloaded from The World Bank website and countries under study are Bangladesh, Bhutan, India, Pakistan and Srilanka. Latest analytics tools like R programming language and matlab have been used to give insight into the important world development indicators and finally the Gross Domestic Product of SAARC nations have been forecasted based on education, health and carbon dioxide emissions with a convincing mean square error of 0.037, using artificial neural networks.

Keywords and Phrases

Data analyticshealtheducationeconomyartificial neural networksworld development indicators.
Reference information

How to Cite

Kavita Pabreja (2016). WORLD DEVELOPMENT INDICATORS ANALYTICS FOR SOUTH ASIAN ASSOCIATION FOR REGIONAL COOPERATION COUNTRIES. South East Asian Journal of Mathematics and Mathematical Sciences, 12(2), 147-160.
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