Centroid of a type-2 fuzzy set
Information Sciences: an International Journal
Subtractive clustering based modeling of job sequencing with parametric search
Fuzzy Sets and Systems - Data analysis
Experimental study of intelligent controllers under uncertainty using type-1 and type-2 fuzzy logic
Information Sciences: an International Journal
Information Sciences: an International Journal
Information Sciences: an International Journal
Optimal fuzzy control system using the cross-entropy method. A case study of a drilling process
Information Sciences: an International Journal
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
An improved method for edge detection based on interval type-2 fuzzy logic
Expert Systems with Applications: An International Journal
Information Sciences: an International Journal
Information Sciences: an International Journal
Fuzzy clustering algorithms for unsupervised change detection in remote sensing images
Information Sciences: an International Journal
TSK fuzzy modeling for tool wear condition in turning processes: An experimental study
Engineering Applications of Artificial Intelligence
Review: Industrial applications of type-2 fuzzy sets and systems: A concise review
Computers in Industry
Type-2 fuzzy neural networks with fuzzy clustering and differential evolution optimization
Information Sciences: an International Journal
Information Sciences: an International Journal
Type-2 fuzzy modeling for acoustic emission signal in precision manufacturing
Modelling and Simulation in Engineering
Type-2 Fuzzy Logic: A Historical View
IEEE Computational Intelligence Magazine
Fuzzy logic = computing with words
IEEE Transactions on Fuzzy Systems
Equalization of nonlinear time-varying channels using type-2 fuzzy adaptive filters
IEEE Transactions on Fuzzy Systems
Impulse Noise Removal From Digital Images by a Detail-Preserving Filter Based on Type-2 Fuzzy Logic
IEEE Transactions on Fuzzy Systems
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In this paper, a micromilling type-2 fuzzy tool condition monitoring system based on multiple AE acoustic emission signal features is proposed. The type-2 fuzzy logic system is used as not only a powerful tool to model acoustic emission signal, but also a great estimator for the ambiguities and uncertainties associated with the signal itself. Using the results of root-mean-square error estimation and the variations in the results of type-2 fuzzy modeling of all signal features, the most reliable ones are selected and integrated into cutting tool life estimation models. The obtained results show that the type-2 fuzzy tool life estimation is in accordance with the cutting tool wear state during the micromilling process. The information about uncertainty prediction of tool life is of great importance for tool condition investigation and crucial when making decisions about maintaining the machining quality.