A New Hybrid Methodology for Nonlinear Time Series Forecasting
Joint Authors
Source
Modelling and Simulation in Engineering
Issue
Vol. 2011, Issue 2011 (31 Dec. 2011), pp.1-5, 5 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2011-08-02
Country of Publication
Egypt
No. of Pages
5
Main Subjects
Abstract EN
Artificial neural networks (ANNs) are flexible computing frameworks and universal approximators that can be applied to a wide range of forecasting problems with a high degree of accuracy.
However, using ANNs to model linear problems have yielded mixed results, and hence; it is not wise to apply them blindly to any type of data.
This is the reason that hybrid methodologies combining linear models such as ARIMA and nonlinear models such as ANNs have been proposed in the literature of time series forecasting.
Despite of all advantages of the traditional methodologies for combining ARIMA and ANNs, they have some assumptions that will degenerate their performance if the opposite situation occurs.
In this paper, a new methodology is proposed in order to combine the ANNs with ARIMA in order to overcome the limitations of traditional hybrid methodologies and yield more general and more accurate hybrid models.
Empirical results with Canadian Lynx data set indicate that the proposed methodology can be a more effective way in order to combine linear and nonlinear models together than traditional hybrid methodologies.
Therefore, it can be applied as an appropriate alternative methodology for hybridization in time series forecasting field, especially when higher forecasting accuracy is needed.
American Psychological Association (APA)
Khashei, Mehdi& Bijari, Mehdi. 2011. A New Hybrid Methodology for Nonlinear Time Series Forecasting. Modelling and Simulation in Engineering،Vol. 2011, no. 2011, pp.1-5.
https://search.emarefa.net/detail/BIM-467377
Modern Language Association (MLA)
Khashei, Mehdi& Bijari, Mehdi. A New Hybrid Methodology for Nonlinear Time Series Forecasting. Modelling and Simulation in Engineering No. 2011 (2011), pp.1-5.
https://search.emarefa.net/detail/BIM-467377
American Medical Association (AMA)
Khashei, Mehdi& Bijari, Mehdi. A New Hybrid Methodology for Nonlinear Time Series Forecasting. Modelling and Simulation in Engineering. 2011. Vol. 2011, no. 2011, pp.1-5.
https://search.emarefa.net/detail/BIM-467377
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-467377