The neural model of the European Union (EU-27) annual growth rates

The EU statistics reveal over 19 million active enterprises within the EU-27’s nonfinancial business economy (defined as industry construction, distributive trades and services, and therefore excluding financial and public services) in 2004. About one third (32.5%) were active in the distributive trades sector which were also relatively labor-intensive activities, accounting for almost 25 % of the EU-27’s non-financial business economy workforce in 2004. In this work we develop a study of the impact of the annual growth rates for industry of the European Union countries on the global annual growth rate of the European Union-27 using neural models between 2004-2008. This research work investigates the possibility to apply neural network modeling for simulation and prediction of the EU-27 global index of production and domestic output price index behavior due to the impact of the same indices of different EU-27’s countries. Therefore we will explore this modeling technique to build the neural model of this complex dynamic economy system. The results obtained by using neural models are more accuracy compared to those obtained by regression methods, and the performance of the neural networks is audacious.