Forecasting Time Series Movement Direction with Hybrid Methodology

المؤلفون المشاركون

Waeto, Salwa
Chuarkham, Khanchit
Intarasit, Arthit

المصدر

Journal of Probability and Statistics

العدد

المجلد 2017، العدد 2017 (31 ديسمبر/كانون الأول 2017)، ص ص. 1-8، 8ص.

الناشر

Hindawi Publishing Corporation

تاريخ النشر

2017-07-31

دولة النشر

مصر

عدد الصفحات

8

التخصصات الرئيسية

الرياضيات

الملخص 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.

نمط استشهاد جمعية علماء النفس الأمريكية (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

نمط استشهاد الجمعية الأمريكية للغات الحديثة (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

نمط استشهاد الجمعية الطبية الأمريكية (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

نوع البيانات

مقالات

لغة النص

الإنجليزية

الملاحظات

Includes bibliographical references

رقم السجل

BIM-1186262