INDUSTRIAL DATA FORECASTING USING DISCRETE WAVELET TRANSFORM

Abstract

Since the industrial data plays significant element in any economic growth and these data have many factors that effect on its behavior.  Therefore, in this article events of productivity of the Extractive Industry in Jordan will be forecasted using some of traditional model which is (ARIMA model) compound with Orthogonal wavelet transform (OWT) in order to improve the forecasting accuracy.  First, the series of dataset will be decomposed by OWT’s then the smooth’s series will be predicted using ARIMA model, OWT+ ARIMA model in order to improve the forecasting accuracy.  As a results the compound model (OWT+ ARIMA) is better than the ARIMA model directly in forecasting accuracy.