Chaotic iterations of fuzzy sets
Fuzzy Sets and Systems - Special issue on mathematical aspects of fuzzy sets
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Information Sciences—Informatics and Computer Science: An International Journal
Centroid of a type-2 fuzzy set
Information Sciences: an International Journal
An Introduction to the Numerical Solution of Differential Equations
An Introduction to the Numerical Solution of Differential Equations
Fuzzy Logic for Embedded Systems Applications
Fuzzy Logic for Embedded Systems Applications
Predicting Chaotic Time Series Using Neural and Neurofuzzy Models: A Comparative Study
Neural Processing Letters
Fuzzy Chaotic Systems: Modeling, Control, and Applications (Studies in Fuzziness and Soft Computing)
Fuzzy Chaotic Systems: Modeling, Control, and Applications (Studies in Fuzziness and Soft Computing)
An efficient centroid type-reduction strategy for general type-2 fuzzy logic system
Information Sciences: an International Journal
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International Journal of Approximate Reasoning
Face Recognition Based on Chaotic Fuzzy RBF Neural Network
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A Novel Type-Reduction Method for Interval Type-2 Fuzzy Logic Systems
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Efficient triangular type-2 fuzzy logic systems
International Journal of Approximate Reasoning
The collapsing method of defuzzification for discretised interval type-2 fuzzy sets
Information Sciences: an International Journal
A hybrid learning algorithm for a class of interval type-2 fuzzy neural networks
Information Sciences: an International Journal
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α-plane representation for type-2 fuzzy sets: theory and applications
IEEE Transactions on Fuzzy Systems
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IEEE Transactions on Fuzzy Systems
Expert Systems with Applications: An International Journal
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IEEE Computational Intelligence Magazine
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IEEE Transactions on Fuzzy Systems
IEEE Transactions on Fuzzy Systems
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IEEE Transactions on Fuzzy Systems
Uncertainty bounds and their use in the design of interval type-2 fuzzy logic systems
IEEE Transactions on Fuzzy Systems
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IEEE Transactions on Fuzzy Systems
Geometric Type-1 and Type-2 Fuzzy Logic Systems
IEEE Transactions on Fuzzy Systems
A transient-chaotic autoassociative network (TCAN) based on Lee oscillators
IEEE Transactions on Neural Networks
Computing the Centroid of a General Type-2 Fuzzy Set by Means of the Centroid-Flow Algorithm
IEEE Transactions on Fuzzy Systems
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International Journal of Approximate Reasoning
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To overcome the complexities in Type-2 Fuzzy Sets (T2FSs) and to present a general model for chaotic FSs, this paper introduces new FSs called Bifurcating FSs (BFSs). The BFS is inspired from human brain. Mathematically, it is equivalent to the coupled chaotic map in which one of the variables is a fuzzy membership function. Biologically, it is equivalent to the oscillatory neuron in which a fuzzy membership function is an activation function for the input neuron. Graphically, it is represented by an input-as-a-bifurcation-parameter diagram. This diagram demonstrates that a BFS can exhibit a wide range of FSs such as convex or non-convex, T1 or T2 and chaotic or non-chaotic FSs, and also make information processing fast. Using a BFS as an activation function in the neurons of the membership layer of a Fuzzy Neural Network (FNN), a new network called a Bifurcating FNN (BFNN) is presented. The proposed network has a similar design to an Interval T2 FNN (IT2FNN). The BFNN is applied to the problem of forecasting Mackey-Glass chaotic time series under different SNRs and different chaotic degrees. In comparison with T1FNNs and IT2FNNs, results show that BFNNs provide more accurate and robust predictions and handle more uncertainties.