Applications of type-2 fuzzy logic systems to forecasting of time-series
Information Sciences—Informatics and Computer Science: An International Journal
Expert Systems with Applications: An International Journal
Fuzzy Interpolative Reasoning Using Interval Type-2 Fuzzy Sets
IEA/AIE '08 Proceedings of the 21st international conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems: New Frontiers in Applied Artificial Intelligence
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Fuzzy multiple attributes group decision-making based on the interval type-2 TOPSIS method
Expert Systems with Applications: An International Journal
Preserving piece-wise linearity in fuzzy interpolation
FUZZ-IEEE'09 Proceedings of the 18th international conference on Fuzzy Systems
IEEE Transactions on Fuzzy Systems
Comprehensive analysis of a new fuzzy rule interpolation method
IEEE Transactions on Fuzzy Systems
IEEE Transactions on Fuzzy Systems
MPEG VBR video traffic modeling and classification using fuzzy technique
IEEE Transactions on Fuzzy Systems
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
Fuzzy interpolative reasoning via scale and move transformations
IEEE Transactions on Fuzzy Systems
Interpolation with function space representation of membership functions
IEEE Transactions on Fuzzy Systems
Interval Type-2 Fuzzy Logic Systems Made Simple
IEEE Transactions on Fuzzy Systems
Uncertain Fuzzy Reasoning: A Case Study in Modelling Expert Decision Making
IEEE Transactions on Fuzzy Systems
Fuzzy Interpolation and Extrapolation: A Practical Approach
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
A Self-Evolving Interval Type-2 Fuzzy Neural Network With Online Structure and Parameter Learning
IEEE Transactions on Fuzzy Systems
Encoding Words Into Interval Type-2 Fuzzy Sets Using an Interval Approach
IEEE Transactions on Fuzzy Systems
IEEE Transactions on Fuzzy Systems
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In recent years, some fuzzy rule interpolation methods have been presented for sparse fuzzy rule-based systems based on interval type-2 fuzzy sets. However, the existing methods have the drawbacks that they cannot guarantee the convexity of the fuzzy interpolated result and may generate the same fuzzy interpolated results with respect to different observations. Moreover, they also cannot deal with fuzzy rule interpolation with bell-shaped interval type-2 fuzzy sets. In this paper, we present a new method for fuzzy rule interpolation for sparse fuzzy rule-based systems based on the ratio of fuzziness of interval type-2 fuzzy sets. The proposed method can overcome the drawbacks of the existing methods. First, it calculates the weights of the closest fuzzy rules with respect to the observation to obtain an intermediate consequence fuzzy set. Then, it uses the ratio of fuzziness of interval type-2 fuzzy sets to infer the fuzzy interpolated result based on the intermediate consequence fuzzy set. We also use some examples to compare the fuzzy interpolated results of the proposed method with the results by the existing methods. The experimental results show that the proposed fuzzy rule interpolation method gets more reasonable results than the existing methods.