Authors : S. Al-Wadi and Abed H. Al-Slaihat
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 study events of productivity of the extractive industry in Jordan will be explored and forecasted using some of traditional model which is (ARIMA Model and exponential 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 functions in order to capture the significant affect based on detailed coefficients, then the smooth’s series will be predicted using ARIMA Model, exponential model, OW+ARIMA Model and Exponential+OWT Model in order to improve the forecasting accuracy.
S. Al-Wadi and Abed H. Al-Slaihat, 2019. Industrial Data Decomposition and Forecasting Using Discrete Wavelet Transform. Journal of Engineering and Applied Sciences, 14: 4303-4306.