A statistical analysis of Type-1 and Interval Type-2 Fuzzy Logic in dynamic parameter adaptation in the Bee Colony Optimization algorithm (BCO) is presented in this paper. The Bee Colony Optimization meta-heuristic belongs to the class of Nature-Inspired Algorithms. The objective of the work is based on the main reasons for the analysis of the approach with Interval Type-2 Fuzzy Logic to find t...

In this paper, we present the interval neutrosophic logics which generalizes the fuzzy logic, paraconsistent logic, intuitionistic fuzzy logic and many other non-classical and non-standard logics. We will give the formal definition of interval neutrosophic propositional calculus and interval neutrosophic predicate calculus. Then we give one application of interval neutrosophic logics to do appr...

This paper presents hardware architecture for an Interval Type-2 fuzzy processor. The architecture is based on the use of two Type-1 Fuzzy Logic Systems (T1 FLS) and it suggests that the existing techniques for implementing T1 FLS can be employed for realizing Type-2 Fuzzy Logic Systems (T2 FLS). The paper also presents a survey of the various realizations for T1 FLS and summarizes them giving ...

A method for designing optimal interval type-2 fuzzy logic controllers using evolutionary algorithms is presented in this paper. Interval type-2 fuzzy controllers can outperform conventional type-1 fuzzy controllers when the problem has a high degree of uncertainty. However, designing interval type-2 fuzzy controllers is more difficult because there are more parameters involved. In this paper, ...

As Granular Computing has gained interest, more research has lead into using different representations for Information Granules, i.e., rough sets, intervals, quotient space, fuzzy sets; where each representation offers different approaches to information granulation. These different representations have given more flexibility to what information granulation can achieve. In this overview paper, ...

Abstract: This paper presents a new general type-2 fuzzy logic method for edge detection applied to color format images. The proposed algorithm combines the methodology based on the image gradients and general type-2 fuzzy logic theory to provide a powerful edge detection method. General type-2 fuzzy inference systems are approximated using the α-planes approach. The edge detection method is te...

This paper presents a literature review of applications using type-2 fuzzy systems in the area of image processing. Over the last years, there has been a significant increase in research on higher-order forms of fuzzy logic; in particular, the use of interval type-2 fuzzy sets and general type-2 fuzzy sets. The idea of making use of higher orders, or types, of fuzzy logic is to capture and repr...

Interval type-2 fuzzy logic system; Interval type-2 fuzzy PID controller; Inverted pendulum system; Hardware-in-the-loop (HIL) simulation Abstract In this study, we propose an embedded real-time interval type-2 fuzzy proportional – integral – derivative (IT2F-PID) controller which is a parallel combination of the interval type-2 fuzzy proportional – integral (IT2F-PI) controller and the interva...

A novel learning methodology based on a hybrid mechanism for training interval singleton type-2 Takagi-SugenoKang fuzzy logic systems uses recursive orthogonal least-squares 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 m...