Why triangular membership functions?
Fuzzy Sets and Systems
Evaluating weapon systems using fuzzy arithmetic operations
Fuzzy Sets and Systems
Forecasting enrollments based on fuzzy time series
Fuzzy Sets and Systems
Applications of type-2 fuzzy logic systems to forecasting of time-series
Information Sciences—Informatics and Computer Science: An International Journal
Forcasting uncertain hotel room demand
Information Sciences: an International Journal
Pattern Recognition with Fuzzy Objective Function Algorithms
Pattern Recognition with Fuzzy Objective Function Algorithms
A hybrid genetic-neural architecture for stock indexes forecasting
Information Sciences: an International Journal - Special issue: Computational intelligence in economics and finance
Newspaper demand prediction and replacement model based on fuzzy clustering and rules
Information Sciences: an International Journal
Locally recurrent neural networks for wind speed prediction using spatial correlation
Information Sciences: an International Journal
Multi-attribute fuzzy time series method based on fuzzy clustering
Expert Systems with Applications: An International Journal
A fuzzy logic approach to forecast energy consumption change in a manufacturing system
Expert Systems with Applications: An International Journal
A bivariate fuzzy time series model to forecast the TAIEX
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Is there a need for fuzzy logic?
Information Sciences: an International Journal
Information Sciences: an International Journal
A distance-based fuzzy time series model for exchange rates forecasting
Expert Systems with Applications: An International Journal
A Fuzzy Asymmetric GARCH model applied to stock markets
Information Sciences: an International Journal
Toward a generalized theory of uncertainty (GTU)--an outline
Information Sciences: an International Journal
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
Expert Systems with Applications: An International Journal
Temperature prediction using fuzzy time series
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
A Multivariate Heuristic Model for Fuzzy Time-Series Forecasting
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Supervised fuzzy clustering for rule extraction
IEEE Transactions on Fuzzy Systems
A generalized concept for fuzzy rule interpolation
IEEE Transactions on Fuzzy Systems
Fuzzy rule interpolation for multidimensional input spaces with applications: a case study
IEEE Transactions on Fuzzy Systems
Interpolation with function space representation of membership functions
IEEE Transactions on Fuzzy Systems
Fuzzy Interpolation and Extrapolation: A Practical Approach
IEEE Transactions on Fuzzy Systems
Enhanced Fuzzy System Models With Improved Fuzzy Clustering Algorithm
IEEE Transactions on Fuzzy Systems
Fuzzy Interpolative Reasoning for Sparse Fuzzy-Rule-Based Systems Based on the Areas of Fuzzy Sets
IEEE Transactions on Fuzzy Systems
IEEE Transactions on Fuzzy Systems
Nonlinear mappings in problem solving and their PSO-based development
Information Sciences: an International Journal
Black hole: A new heuristic optimization approach for data clustering
Information Sciences: an International Journal
Forecasting the TAIEX based on fuzzy time series, PSO techniques and support vector machines
ACIIDS'13 Proceedings of the 5th Asian conference on Intelligent Information and Database Systems - Volume Part I
Fuzzy spline interpolation with optimal property in parametric form
Information Sciences: an International Journal
Core set analysis in inconsistent decision tables
Information Sciences: an International Journal
Information Sciences: an International Journal
Water leakage forecasting: the application of a modified fuzzy evolving algorithm
Applied Soft Computing
An adaptive robust fuzzy beamformer for steering vector mismatch and reducing interference and noise
Information Sciences: an International Journal
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In this paper, we present a new method for multi-variable fuzzy forecasting based on fuzzy clustering and fuzzy rule interpolation techniques. First, the proposed method constructs training samples based on the variation rates of the training data set and then uses the training samples to construct fuzzy rules by making use of the fuzzy C-means clustering algorithm, where each fuzzy rule corresponds to a given cluster. Then, we determine the weight of each fuzzy rule with respect to the input observations and use such weights to determine the predicted output, based on the multiple fuzzy rules interpolation scheme. We apply the proposed method to the temperature prediction problem and the Taiwan Stock Exchange Capitalization Weighted Stock Index (TAIEX) data. The experimental results show that the proposed method produces better forecasting results than several existing methods.