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 new fuzzy time-series model of fuzzy number observations
Fuzzy Sets and Systems
Triangular-norm-based addition of fuzzy intervals
Fuzzy Sets and Systems - Special issue: fuzzy arithmetic
Fuzzy ARIMA model for forecasting the foreign exchange market
Fuzzy Sets and Systems
Fuzzy least-squares linear regression analysis using shape preserving operations
Information Sciences—Informatics and Computer Science: An International Journal
A Fuzzy agent-based model for reduction of bullwhip effect in supply chain systems
Expert Systems with Applications: An International Journal
Improved time-variant fuzzy time series forecast
Fuzzy Optimization and Decision Making
Expert Systems with Applications: An International Journal
An improved fuzzy forecasting method for seasonal time series
Expert Systems with Applications: An International Journal
Revenue forecasting using a least-squares support vector regression model in a fuzzy environment
Information Sciences: an International Journal
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Recently, Song et al. [Fuzzy Sets and Systems 73 (1995) 341-348] proposed a homogeneous fuzzy time series model to model dynamic process whose observations are fuzzy sets or linguistic values by means of defining some new operations on fuzzy numbers. In this paper, we considered expanding the results to the nonhomogeneous fuzzy time series and the general fuzzy time series by using the weakest t-norm based algebraic fuzzy operations and solved the open problem suggested by Song et al. in their conclusion of the paper.