Bivariate Long Term Fuzzy Time Series Forecasting of Dry Cargo Freight Rates

다국어 초록 (Multilingual Abstract)

This paper proposes a bivariate long term fuzzy inference system for time series forecasting task in the eld of freight market. Fuzzy time series methods are applied by many scholars and it is broadly accepted pattern recognition and forecasting tool. Previous studies mainly establish algorithms for high requency time series data such as daily and monthly intervals. The proposed model performs similar techniques for long term annual base data and also extends the conventional method with multi-variate heuristic algorithm.
Empirical work is accomplished on shipping freight rate data and life expectancy is used as a leading indicator in the bivariate fuzzy time series model.

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