In recent years, the type-2 fuzzy sets theory has been used to model and minimize the effects of uncertainties in rule-base fuzzy logic system (FLS). In order to make the type-2 FLS reasonable and reliable, a new simple and novel statistical method to decide interval-valued fuzzy membership functions and probability type reduce reasoning method for the interval-valued FLS are developed. We have...

This article concerns a connection of fuzzy logic and lattice theory. Namely, the fuzzy sets form a Heyting lattice with union and intersection of fuzzy sets as meet and join operations. The lattice of fuzzy sets is defined as the product of interval posets. As the final result, we have characterized the composition of fuzzy relations in terms of lattice theory and proved its associativity.

This paper presents research on applications of fuzzy logic and higher-order fuzzy logic systems to control filters reducing air pollution [1]. The filters use Selective Catalytic Reduction (SCR) method and, as for now, this process is controlled manually by a human expert. The goal of the research is to control an SCR system responsible for emission of nitrogen oxide (NO) and nitrogen dioxide ...

This chapter maps out the development of the PSO based Functional Link Interval Type-2 Fuzzy Neural System (FLIT2FNS) model used to forecast the stock market indices. In the process, it discusses the architecture of Functional Link Artificial Neural Network (FLANN), FLANN & Type-1Fuzzy Logic System (Type1FLS) and the differences between Type-1FLS and Interval Type-2 Fuzzy Logic System (IT2FLS)....

Interval type-2 fuzzy logic systems have a wide range of applications due to their abilities to handle uncertainties compared to their type-1 counterparts. This paper presents an approach for developing closed-form mathematical representations for interval type-2 fuzzy logic systems. Having such a representation can be useful in real-time implementation of the system and in its mathematical ana...

A method for response integration in modular neural networks with type-2 fuzzy logic for biometric systems p. 5 Evolving type-2 fuzzy logic controllers for autonomous mobile robots p. 16 Adaptive type-2 fuzzy logic for intelligent home environment p. 26 Interval type-1 non-singleton type-2 TSK fuzzy logic systems using the hybrid training method RLS-BP p. 36 An efficient computational method to...

ress as: , Alexa and hosti 013.11.0 Abstract The interval type-2 fuzzy logic controller (IT2-FLC) is able to model and minimize the numerical and linguistic uncertainties associated with the inputs and outputs of a fuzzy logic system (FLS). This paper proposes an interval type-2 fuzzy PD (IT2F-PD) controller for nonlinear inverted pendulum. The proposed controller uses the Mamdani interval type...