A combination of traditional time series forecasting models with fuzzy learning neural networks

Discusses a combined model of three traditional time series forecasting (TSF) models, which involves a regression model, an exponential smoothing model and a gray forecasting model, using neural networks (NNs) to assemble them based on a fuzzy learning algorithm. Finally we represent an example of a TSF financial application in telecom enterprises to show its improvement in forecasting accuracy.