Universiti Teknologi Malaysia Institutional Repository

Implementation of fuzzy time series in forecasting of the non-stationary data

Efendi, R. and Deris, M. M. and Ismail, Z. (2016) Implementation of fuzzy time series in forecasting of the non-stationary data. International Journal of Computational Intelligence and Applications, 15 (2). ISSN 1469-0268

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Abstract

To forecast the non-stationary data is quite difficult when compared with the stationary data time series. Because their variances are not constant and not stable like the second data type. This paper presents the implementation of fuzzy time series (FTS) into the non-stationary time series data forecasting, such as, the electricity load demand, the exchange rates, the enrollment university and others. These data forecasts are derived by implementing of the weightage and linguistic out-sample methods. The result shows that the FTS can be applied in improving the accuracy and efficiency of these non-stationary data forecasting opportunities.

Item Type:Article
Uncontrolled Keywords:Finance, Forecasting, Electricity load, enrollment, Exchange rates, Fuzzy time series, Nonstationary data, Time series
Subjects:Q Science > QA Mathematics
Divisions:Science
ID Code:72467
Deposited By: Narimah Nawil
Deposited On:26 Nov 2017 03:37
Last Modified:26 Nov 2017 03:37

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