Although time series analyses is effectively used in forecasting customer demands and resource planning, there are some factors that limits the validity of these analysyses (such as big sample volume, normal distribution and inability of using linguistic concepts). Fuzzly cluster theory and fuzzy logiz which was proposed by Zaheh, provided a methodology which handles uncertainty and ambiguity in linguistic data. Firstly, Song and Chissom proposed first order fuzzy time series model. After that many models were proposed in order to eliminate the calculation difficulty of the model and improve the forecasting accuracy of the model. Chen (1996), Hwang et al. (1998) and Chen (2002) proposed the main fuzzy forecasting models in this field. The aim of this study is to apply the stated three models to the periodic sales data and compare the three Fuzzy Time Series Models in terms of reliability of the models
Benzer Makaleler | Yazar | # |
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