Adaptive fuzzy systems and control: design and stability analysis
Adaptive fuzzy systems and control: design and stability analysis
Neuro-fuzzy and soft computing: a computational approach to learning and machine intelligence
Neuro-fuzzy and soft computing: a computational approach to learning and machine intelligence
Information Sciences: an International Journal
Experimental study of intelligent controllers under uncertainty using type-1 and type-2 fuzzy logic
Information Sciences: an International Journal
Uncertainty measures for interval type-2 fuzzy sets
Information Sciences: an International Journal
Design of interval type-2 fuzzy sliding-mode controller
Information Sciences: an International Journal
Hybrid Learning Algorithm for Interval Type-2 Fuzzy Neural Networks
GRC '07 Proceedings of the 2007 IEEE International Conference on Granular Computing
An efficient centroid type-reduction strategy for general type-2 fuzzy logic system
Information Sciences: an International Journal
On similarity and inclusion measures between type-2 fuzzy sets with an application to clustering
Computers & Mathematics with Applications
Information Sciences: an International Journal
Information Sciences: an International Journal
Information Sciences: an International Journal
A hybrid learning algorithm for a class of interval type-2 fuzzy neural networks
Information Sciences: an International Journal
Information Sciences: an International Journal
Interval type-2 fuzzy logic and modular neural networks for face recognition applications
Applied Soft Computing
Fundamentals of a fuzzy-logic-based generalized theory of stability
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics - Special issue on cybernetics and cognitive informatics
On constructing parsimonious type-2 fuzzy logic systems via influential rule selection
IEEE Transactions on Fuzzy Systems
IEEE Transactions on Fuzzy Systems
Transformation between type-2 TSK fuzzy systems and an uncertain Gaussian mixture model
Soft Computing - A Fusion of Foundations, Methodologies and Applications
A modified gradient-based neuro-fuzzy learning algorithm and its convergence
Information Sciences: an International Journal
Takagi-Sugeno fuzzy model based indirect adaptive fuzzy observer and controller design
Information Sciences: an International Journal
On the stability of interval type-2 TSK fuzzy logic control systems
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics - Special issue on game theory
A type-2 fuzzy ontology and its application to personal diabetic-diet recommendation
IEEE Transactions on Fuzzy Systems
Relaxed stabilization conditions for continuous-time Takagi-Sugeno fuzzy control systems
Information Sciences: an International Journal
IEEE Transactions on Fuzzy Systems - Special section on computing with words
An improved method for edge detection based on interval type-2 fuzzy logic
Expert Systems with Applications: An International Journal
Toward general type-2 fuzzy logic systems based on zSlices
IEEE Transactions on Fuzzy Systems
IEEE Transactions on Fuzzy Systems
Review: Industrial applications of type-2 fuzzy sets and systems: A concise review
Computers in Industry
On the robustness of Type-1 and Interval Type-2 fuzzy logic systems in modeling
Information Sciences: an International Journal
Type-2 fuzzy neural networks with fuzzy clustering and differential evolution optimization
Information Sciences: an International Journal
Expert Systems with Applications: An International Journal
Interval Type-2 fuzzy voter design for fault tolerant systems
Information Sciences: an International Journal
Hierarchical type-2 neuro-fuzzy BSP model
Information Sciences: an International Journal
Type-2 fuzzy description logic
Frontiers of Computer Science in China
Fire-rule-based direct adaptive type-2 fuzzy H∞ tracking control
Engineering Applications of Artificial Intelligence
Information Sciences: an International Journal
Stability Analysis of Interval Type-2 Fuzzy-Model-Based Control Systems
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Interval type-2 fuzzy logic systems: theory and design
IEEE Transactions on Fuzzy Systems
IEEE Transactions on Fuzzy Systems
A hierarchical type-2 fuzzy logic control architecture for autonomous mobile robots
IEEE Transactions on Fuzzy Systems
On the Continuity of Type-1 and Interval Type-2 Fuzzy Logic Systems
IEEE Transactions on Fuzzy Systems
An Enhanced Type-Reduction Algorithm for Type-2 Fuzzy Sets
IEEE Transactions on Fuzzy Systems
Robust stability of impulsive Takagi-Sugeno fuzzy systems with parametric uncertainties
Information Sciences: an International Journal
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
A new indirect approach to the type-2 fuzzy systems modeling and design
Information Sciences: an International Journal
Hi-index | 0.07 |
A proposed learning methodology based on a hybrid mechanism for training interval A2-C1 type-2 non-singleton type-2 Takagi-Sugeno-Kang fuzzy logic systems uses a recursive square-root filter to tune the type-1 consequent parameters and the steepest descent method to tune the interval type-2 antecedent parameters. The proposed hybrid-learning algorithm changes the interval type-2 model parameters adaptively to minimize some criterion function as new information becomes available and to match desired input-output data pairs. Its antecedent sets are type-2 fuzzy sets, its consequent sets are type-1 fuzzy sets, and its inputs are interval type-2 non-singleton fuzzy numbers with uncertain standard deviations. As reported in the literature, the performance indices of hybrid models have proved to be better than those of the individual training mechanisms used alone. Comparison with non-hybrid interval A2-C1 type-2 Takagi-Sugeno-Kang fuzzy logic systems and with non-hybrid A1-C0 type-1 Takagi-Sugeno-Kang fuzzy logic systems shows that the proposed hybrid mechanism is a well-performing non-linear adaptive method that enables the interval type-2 fuzzy model to match an unknown non-linear mapping and to converge very fast. Experiments were carried out involving the application of the hybrid interval A2-C1 type-2 non-singleton type-2 Takagi-Sugeno-Kang fuzzy logic systems for modeling and prediction of the scale-breaker entry temperature in a hot strip mill for three different types of coils. The results demonstrate how the interval type-2 fuzzy system learns from selected input-output data pairs and improves its performance as hybrid training progresses.