Fuzzy time series and its models
Fuzzy Sets and Systems
Forecasting enrollments with fuzzy time series—part I
Fuzzy Sets and Systems
Forecasting enrollments with fuzzy time series—part II
Fuzzy Sets and Systems
A comparison of fuzzy forecasting and Markov modeling
Fuzzy Sets and Systems
Forecasting enrollments based on fuzzy time series
Fuzzy Sets and Systems
Handling forecasting problems using fuzzy time series
Fuzzy Sets and Systems
Time Series Analysis, Forecasting and Control
Time Series Analysis, Forecasting and Control
An improved fuzzy time series forecasting method using trapezoidal fuzzy numbers
Fuzzy Optimization and Decision Making
Fuzzy time-series based on adaptive expectation model for TAIEX forecasting
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Fuzzy dual-factor time-series for stock index forecasting
Expert Systems with Applications: An International Journal
Temperature prediction using fuzzy time series
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Multi-variable fuzzy forecasting based on fuzzy clustering and fuzzy rule interpolation techniques
Information Sciences: an International Journal
Expert Systems with Applications: An International Journal
Modeling seasonality using the fuzzy integrated logical forecasting (FILF) approach
Expert Systems with Applications: An International Journal
Hi-index | 12.05 |
This study develops an improved fuzzy time series method via adjustment of the latest value factor and previous error patterns. There are many fuzzy extended applications in the literature, and the fuzzy time series is one successful implementation of fuzzy logical modelling. Fuzzy time series have been studied for over a decade, and many researchers have proposed to remove some of the drawbacks of the initial fuzzy time series algorithm. In this paper, fuzzy integrated logical forecasting (FILF) and extended FILF (E-FILF) algorithms are suggested for short term forecasting purposes. Empirical studies are performed over the Baltic Dry Index (BDI), and indicate the superiority of the proposed approach compared to conventional benchmark methods.