Petroleum demand forecasting for Taiwan using modified fuzzy-grey algorithms

In this paper, we adopt the exponentially weighted moving average (EWMA) method to develop the residual modification EWMA grey forecasting model REGM(1,1) and combines it with fuzzy theory to derive the fuzzy REGM or the FREGM(1,1) model. The proposed model is used to forecast annual petroleum deman...

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Bibliographic Details
Published in:Expert systems Vol. 33; no. 1; pp. 60 - 69
Main Authors: Lu, Shin-Li, Tsai, Chen-Fang
Format: Journal Article
Language:English
Published: Oxford Blackwell Publishing Ltd 01.02.2016
Subjects:
Algorithms
Analysis
Crude oil
Demand
Economic forecasting
Errors
EWMA
Expert systems
Forecasting techniques
Fuzzy
Fuzzy logic
fuzzy theory
grey forecast
Mathematical models
Petroleum
petroleum demand
Studies
Taiwan
ISSN:0266-4720, 1468-0394
Online Access:Get full text
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Summary:In this paper, we adopt the exponentially weighted moving average (EWMA) method to develop the residual modification EWMA grey forecasting model REGM(1,1) and combines it with fuzzy theory to derive the fuzzy REGM or the FREGM(1,1) model. The proposed model is used to forecast annual petroleum demand in Taiwan. The experimental results show that the mean absolute percentage errors, median absolute percentage error, and symmetric mean absolute percentage error of FREGM(1,1) model are higher by 23.71, 12.26, and 23.06% respectively, compared with those obtained using the traditional GM(1,1) model.
Bibliography:ArticleID:EXSY12129
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ISSN:0266-4720
1468-0394
DOI:10.1111/exsy.12129