A Statistical Method for Fuzzy Time Series Forecasting Based on the Class Length in Tea Production
Keywords:
Interval length, Fuzzy time series, Forecasting, Yule rule, MSEAbstract
Fuzzy forecasting time series is a method of foreseeing the anticipated data in situation in which a form of different time series is envisioned and the information is vague and imprecise. This study emphasis a new method which is used for fuzzy forecasting time
series based on the class length and coefficient of variation is also used in the calculating forecasting values. The new method is examined on the tea production data of TATA Consumer Products Limited, Kerala. This new proposed technique is compared with the existing approaches to ascertain the efficacy in relations to mean square error (MSE) and the average forecasting error (AFE).
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