Until recently, local governments in Spain were using machines with rolling cylinders for verifying taximeters. However, the condition of the tires can lead to errors in the proces...
—Reinforcement learning (RL) is a valuable learning method when the systems require a selection of control actions whose consequences emerge over long periods for which input– ...
The word Interpretability is becoming more and more frequent in the fuzzy literature. It is admitted as the main advantage of fuzzy systems and it should be given a main role in fu...
This paper proposes a type-2 self-organizing neural fuzzy system (T2SONFS) and its hardware implementation. The antecedent parts in each T2SONFS fuzzy rule are interval type-2 fuzz...
The relationship between support vector machines (SVMs) and Takagi–Sugeno–Kang (TSK) fuzzy systems is shown. An exact representation of SVMs as TSK fuzzy systems is given for ...
Juan Luis Castro, L. D. Flores-Hidalgo, Carlos Jav...
In this paper, in order to reduce the explosive increase of the search space as the input dimension grows, we present a new representation method for the structure of fuzzy rules, ...
: The definition of the Fuzzy Rule Base is one of the most important and difficult tasks when designing Fuzzy Systems. This paper discusses the results of two different hybrid meth...
Marcos Evandro Cintra, Heloisa de Arruda Camargo, ...
In this paper we propose a new nonparametric regression algorithm based on Fuzzy systems with overlapping concepts. We analyze its consistency properties, showing that it is capab...
One of the superior capabilities of fuzzy systems is that they can use the information expressed in a linguistic pattern. Though most fuzzy systems, have been formed to emulate hu...
This paper describes a method for formal compression of fuzzy systems. This method compresses a fuzzy system with an arbitrarily large number of rules into a smaller fuzzy system ...