Efendi, Riswan and Ismail, Zuhaimy and Mat Deris, Mustafa (2015) "A new linguistic out-sample approach of fuzzy time series for daily forecasting of Malaysian electricity load demand". Applied Soft Computing, 28. pp. 422-430. ISSN ISSN: 1568-4946

Preview

Text A new linguistic out-sample approach of fuzzy time series for daily__forecasting of Malaysian electricity load demand.pdf - Published Version Download (1MB) | Preview

Abstract

The fuzzy logical relationships and the midpoints of interval have been used to determine the numerical in-out-samples forecast in the fuzzy time series modeling. However, the absolute percentage error is still yet significantly improved. This can be done where the linguistics time series values should be forecasted inthe beginning before thenumericalforecasted values obtained. This paper introduces thenew approach in determining the linguistic out-sample forecast by using the index numbers of linguistics approach. Moreover, the weights of fuzzy logical relationships are also suggested to compensate the presence of bias in the forecasting. The daily load data from National Electricity Board (TNB) of Malaysia is used as an empirical study and the reliability of the proposed approach is compared with the approach proposed by Yu. The result indicates that the mean absolute percentage error (MAPE) of the proposed approach is smaller than that as proposed by Yu. By using this approach the linguistics time series forecasting and the numerical time series forecasting can be resolved Keywords: Fuzzy time series Index number Weight Electricity load demand Linguistic time series Out-sample forecast

Actions (login required)

View Item