Forecasting Time Series Movement Direction with Hybrid Methodology
Joint Authors
Waeto, Salwa
Chuarkham, Khanchit
Intarasit, Arthit
Source
Journal of Probability and Statistics
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-8, 8 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-07-31
Country of Publication
Egypt
No. of Pages
8
Main Subjects
Abstract EN
Forecasting the tendencies of time series is a challenging task which gives better understanding.
The purpose of this paper is to present the hybrid model of support vector regression associated with Autoregressive Integrated Moving Average which is formulated by hybrid methodology.
The proposed model is more convenient for practical usage.
The tendencies modeling of time series for Thailand’s south insurgency is of interest in this research article.
The empirical results using the time series of monthly number of deaths, injuries, and incidents for Thailand’s south insurgency indicate that the proposed hybrid model is an effective way to construct an estimated hybrid model which is better than the classical time series model or support vector regression.
The best forecast accuracy is performed by using mean square error.
American Psychological Association (APA)
Waeto, Salwa& Chuarkham, Khanchit& Intarasit, Arthit. 2017. Forecasting Time Series Movement Direction with Hybrid Methodology. Journal of Probability and Statistics،Vol. 2017, no. 2017, pp.1-8.
https://search.emarefa.net/detail/BIM-1186262
Modern Language Association (MLA)
Waeto, Salwa…[et al.]. Forecasting Time Series Movement Direction with Hybrid Methodology. Journal of Probability and Statistics No. 2017 (2017), pp.1-8.
https://search.emarefa.net/detail/BIM-1186262
American Medical Association (AMA)
Waeto, Salwa& Chuarkham, Khanchit& Intarasit, Arthit. Forecasting Time Series Movement Direction with Hybrid Methodology. Journal of Probability and Statistics. 2017. Vol. 2017, no. 2017, pp.1-8.
https://search.emarefa.net/detail/BIM-1186262
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1186262