Crude Oil Forecasting with an Improved Model Based on Wavelet Transform and Support Vector Machines
نویسندگان
چکیده
This paper presents a hybrid wavelet support vector machines (WSVM) model that combines both wavelet technique and the SVM model for crude oil forecasting. Based on the purpose, the main time series was decomposed to some multi-frequently time series by wavelet theory and these time series were imposed as input data to the SVM for forecasting of crude oil series. To assess the effectiveness of this model, daily crude oil market-West Texas Intermediate (WTI) has been used as the case study. Time series prediction capability performance of the WSVM model is compared with the single SVM model using various statistics measures. As seen in comparison, WSVM yielded more accurate than of any individual model and offered a practical solution to the problem in crude oil forecasting.
منابع مشابه
Crude Oil Price Forecasting with an Improved Model Based on Wavelet Transform and Support Vector Machines
This paper presents a hybrid wavelet support vector machines (WSVM) model that combines both wavelet technique and the SVM model for crude oil price forecasting. Based on the purpose, the main time series was decomposed to some multi-frequently time series by wavelet theory and these time series were imposed as input data to the SVM for forecasting of crude oil price series. To assess the effec...
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