دانلود رایگان مقاله یک رگرسیون بردار پشتیبانی ICA برای پیش بینی قیمت های نفت خام

عنوان فارسی
یک رگرسیون بردار پشتیبانی ICA برای پیش بینی قیمت های نفت خام
عنوان انگلیسی
An ICA-based support vector regression scheme for forecasting crude oil prices
صفحات مقاله فارسی
0
صفحات مقاله انگلیسی
9
سال انتشار
2016
نشریه
الزویر - Elsevier
فرمت مقاله انگلیسی
PDF
کد محصول
E4684
رشته های مرتبط با این مقاله
مهندسی نفت
گرایش های مرتبط با این مقاله
نفت خام
مجله
پیش بینی فنی و تغییر اجتماعی - Technological Forecasting & Social Change
دانشگاه
دانشکده بازرگانی، دانشگاه هوهی، چین
کلمات کلیدی
قیمت نفت خام، پیش بینی، تجزیه و تحلیل جزء مستقل، رگرسیون بردار پشتیبانی
۰.۰ (بدون امتیاز)
امتیاز دهید
چکیده

abstract


The fluctuations of crude oil prices affect the economic growth of importing and exporting countries as well as regional security and stability. The intrinsic complex features of oil prices and the uncertainty in economic policy pose challenge on the accurate forecasting of crude oil prices. This paper employs independent component analysis (ICA) to analyze crude oil prices which are decomposed into several independent components corresponding to different types of influential factors affecting oil price. We also propose a novel ICA-based support vector regression scheme, namely ICA-SVR2 , for forecasting crude oil prices. The ICA-SVR2 starts from the use of ICA to decompose oil price series into three independent components, which are respectively forecasted by SVR models. The forecasted independent components are then integrated together by developing a new SVR model with independent components as inputs for forecasting crude oil prices. Our experimental results show the usefulness of ICA in identifying the driving factors behind the fluctuations of crude oil prices. A comparative study between ICA-SVR2 and other two models shows that ICA-SVR2 is an effective tool in forecasting crude oil prices.

نتیجه گیری

4. Conclusions


This paper proposes to use ICA to analyze crude oil prices and develops an ICA-based SVR (ICA-SVR2 ) scheme for forecasting crude oil prices. ICA is helpful to identify the hidden factors behind the fluctuations of international crude oil prices. The proposed ICA-SVR2 model starts from the use of ICA to decompose four international oil price series into three independent components. Then we build three SVR models to forecast the three independent components, respectively. Based on the three independent components as well as the WTI crude oil price series, we construct one integrated SVR model to forecast crude oil prices. Our experimental results show that the integration of ICA with SVR can improve the forecasting accuracy of SVR significantly. Another advantage of ICA is that the independent components obtained may shed insights on understanding the driving forces behind crude oil prices.


بدون دیدگاه