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

Mathematics

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