Approximation and Prediction of Wages Based on Granular Neural Network

This article offers a detailed computational algorithm used in that type of neural networks, extends their applications to fit and predict the data of wages time series, conducts experiments and indicates the gain of granular neural networks, specifically conducting experimentation using the classical (statistical) or econometric methods and conventional/soft RBF neural networks. Results are analysed and opportunities for future research are suggested.