OWA based Fuzzy Time Series Forecasting Model

In this paper we have proposed Fuzzy Time Series and Ordered Weight Aggregation (OWA) based forecasting model. Accuracy is one of the most important factors when dealing with forecasts. Accuracy depends on relative weight of past observations used to predict forecasted value. Method of aggregation of past observation is important factor in forecasting models where next prediction depends only on past observations. OWA has been proved most efficient tool for aggregation of data. In this study, aggregation of fuzzy relationships generated at prior times (t, t-1, t-2) is performed using OWA to predict value at time t+1. Experimental study reveals how OWA coalesce with fuzzy time series to design forecasting model. It can be observed from comparative study that use of OWA considerably reduces Mean Square Error (MSE) and Mean Absolute Percentage Error (MAPE). KeywordsForecasting, Fuzzy, Aggregation, Time Series

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