Reduction fuzzy social computing for gross national income cross-country comparison

An economic activity analysis carried out by employing the fuzzy dimensional size reduction is proposed in this paper. The need for economic impact monitoring is important to measure the economic growth and the effectiveness of worldwide or locally economic policy or activity. The fuzzy dimensional size reduction is employed in synergy with the fuzzy social computing, which is used to describe and model social relations. When working together they form the reduction fuzzy social computing that employs fuzzy particles to represent individuals, nations, companies and so forth. In this paper, the diverse gross national income (GNI)-type economic indicators are employed for practical economic activity assessment. World Bank supplies empirical data for exemplifying the potential of the proposed approach. Such an approach merges them into a simple graphic and a multidimensional abstract modeling for economic performance analyses and comparisons. The reduction of multidimensional data associated to fuzzy social computing enables data analyses and economic performance assessment in a simplified manner.