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
Non-linear modelling and forecasting of S&P 500 volatility
Mathematics and Computers in Simulation - Selected papers of the MSSANZ/IMACS 13th biennial conference on modelling and simulation, Hamilton, New Zealand, December 1999
Temperature prediction using fuzzy time series
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Ratio-based lengths of intervals to improve fuzzy time series forecasting
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Forecasting enrollments using automatic clustering techniques and fuzzy logical relationships
Expert Systems with Applications: An International Journal
A neural network-based fuzzy time series model to improve forecasting
Expert Systems with Applications: An International Journal
Adaptive-expectation based multi-attribute FTS model for forecasting TAIEX
Computers & Mathematics with Applications
Temperature prediction based on fuzzy clustering and fuzzy rules interpolation techniques
SMC'09 Proceedings of the 2009 IEEE international conference on Systems, Man and Cybernetics
Multi-variable fuzzy forecasting based on fuzzy clustering and fuzzy rule interpolation techniques
Information Sciences: an International Journal
Weighted fuzzy time series forecasting model
ACIIDS'10 Proceedings of the Second international conference on Intelligent information and database systems: Part I
Forecast Combination by Using Artificial Neural Networks
Neural Processing Letters
Time series labeling algorithms based on the K-nearest neighbors' frequencies
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Fuzzy time series forecasting method based on Gustafson-Kessel fuzzy clustering
Expert Systems with Applications: An International Journal
Multivariate fuzzy forecasting based on fuzzy time series and automatic clustering techniques
Expert Systems with Applications: An International Journal
The adaptive fuzzy time series model with an application to Taiwan's tourism demand
Expert Systems with Applications: An International Journal
Forecasting neural network-based fuzzy time series with different neural network models
GAVTASC'11 Proceedings of the 11th WSEAS international conference on Signal processing, computational geometry and artificial vision, and Proceedings of the 11th WSEAS international conference on Systems theory and scientific computation
Forecasting shanghai composite index based on fuzzy time series and improved C-fuzzy decision trees
Expert Systems with Applications: An International Journal
Fuzzy time series model incorporating predictor variables and interval partition
WSEAS Transactions on Mathematics
Partitions based computational method for high-order fuzzy time series forecasting
Expert Systems with Applications: An International Journal
A new time-invariant fuzzy time series forecasting method based on genetic algorithm
Advances in Fuzzy Systems - Special issue on Fuzzy Function, Relations, and Fuzzy Transforms (2012)
Expert Systems with Applications: An International Journal
High-order fuzzy-neuro expert system for time series forecasting
Knowledge-Based Systems
An efficient time series forecasting model based on fuzzy time series
Engineering Applications of Artificial Intelligence
The modeling of time series based on fuzzy information granules
Expert Systems with Applications: An International Journal
Two new time-variant methods for fuzzy time series forecasting
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
Advances in Fuzzy Systems
Hi-index | 12.07 |
Traditional time series methods can predict the seasonal problem, but fail to forecast the problems with linguistic value. An alternative forecasting method such as fuzzy time series is utilized to deal with these kinds of problems. Two shortcomings of the existing fuzzy time series forecasting methods are that they lack persuasiveness in determining universe of discourse and the length of intervals, and that they lack objective method for multiple-attribute fuzzy time series. This paper introduces a novel multiple-attribute fuzzy time series method based on fuzzy clustering. The methods of fuzzy clustering are integrated in the processes of fuzzy time series to partition datasets objectively and enable processing of multiple attributes. For verification, this paper uses two datasets: (1) the yearly data on enrollments at the University of Alabama, and (2) the Taiwan Stock Exchange Capitalization Weighted Stock Index (TAIEX) futures. The forecasting results show that the proposed method can forecast not only one-attribute but also multiple-attribute data effectively and outperform the listing methods.