Unsupervised Optimal Fuzzy Clustering
IEEE Transactions on Pattern Analysis and Machine Intelligence
Fuzzy time series and its models
Fuzzy Sets and Systems
Forecasting enrollments with fuzzy time series—part I
Fuzzy Sets and Systems
Forecasting enrollments based on fuzzy time series
Fuzzy Sets and Systems
Development of a cost function for wastewater treatment systems with fuzzy regression
Fuzzy Sets and Systems
Forecasting Stock Price Index Using Fuzzy Time-Series Based on Rough Set
FSKD '07 Proceedings of the Fourth International Conference on Fuzzy Systems and Knowledge Discovery - Volume 03
Fuzzy time-series based on adaptive expectation model for TAIEX forecasting
Expert Systems with Applications: An International Journal
A FCM-based deterministic forecasting model for fuzzy time series
Computers & Mathematics with Applications
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
A new approach for determining the length of intervals for fuzzy time series
Applied Soft Computing
Modified Gath--Geva clustering for fuzzy segmentation of multivariate time-series
Fuzzy Sets and Systems
Finding an optimal interval length in high order fuzzy time series
Expert Systems with Applications: An International Journal
Frequency-weighted fuzzy time-series based on fibonacci sequence for TAIEX forecasting
PAKDD'07 Proceedings of the 2007 international conference on Emerging technologies in knowledge discovery and data mining
Fuzzy forecasting based on fuzzy-trend logical relationship groups
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Adaptive time-variant models for fuzzy-time-series forecasting
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Fuzzy time series prediction using hierarchical clustering algorithms
Expert Systems with Applications: An International Journal
A new approach based on the optimization of the length of intervals in fuzzy time series
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
Abstraction and specialization of information granules
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Recursive information granulation: aggregation and interpretation issues
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
Information Sciences: an International Journal
Information Sciences: an International Journal
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Partitioning the universe of discourse and determining intervals containing useful temporal information and coming with better interpretability are critical for forecasting in fuzzy time series. In the existing literature, researchers seldom consider the effect of time variable when they partition the universe of discourse. As a result, and there is a lack of interpretability of the resulting temporal intervals. In this paper, we take the temporal information into account to partition the universe of discourse into intervals with unequal length. As a result, the performance improves forecasting quality. First, time variable is involved in partitioning the universe through Gath-Geva clustering-based time series segmentation and obtain the prototypes of data, then determine suitable intervals according to the prototypes by means of information granules. An effective method of partitioning and determining intervals is proposed. We show that these intervals carry well-defined semantics. To verify the effectiveness of the approach, we apply the proposed method to forecast enrollment of students of Alabama University and the Taiwan Stock Exchange Capitalization Weighted Stock Index. The experimental results show that the partitioning with temporal information can greatly improve accuracy of forecasting. Furthermore, the proposed method is not sensitive to its parameters.