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

Efendi, Riswan and Mat Deris, Mustafa and Ismail, Zuhaimy (2016) Implementation of fuzzy time series in forecasting of the non-stationary data. International Journal of Computational Intelligence and Applications, 15 (2).

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Abstract

To forecast the non-stationary data is quite di±cult 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 e±ciency of these non-stationary data forecasting opportunities.

Item Type:Article
Uncontrolled Keywords:Fuzzy time series; non-stationary data; electricity load; exchange rates; enrollment
Subjects:Q Science > QA Mathematics > QA76 Computer software
Divisions:Faculty of Computer Science and Information Technology > Department of Software Engineering
ID Code:8552
Deposited By:Mr. Mohammad Shaifulrip Ithnin
Deposited On:21 Jun 2017 11:43
Last Modified:21 Jun 2017 11:43

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