This paper presents a review of the central theories involved in hybrid models based on
fuzzy systems and artificial neural networks, mainly focused on supervised methods for …

A review of the applications of interval type-2 fuzzy logic in intelligent control has been
considered in this paper. The fundamental focus of the paper is based on the basic reasons …

This paper proposes a genetic algorithm-based method for sizing the energy storage system
(ESS) in microgrids. The main goal of the proposed method is to find the energy and power …

An evolutionary recurrent network which automates the design of recurrent neural/fuzzy
networks using a new evolutionary learning algorithm is proposed in this paper. This new …

The need for trading off interpretability and accuracy is intrinsic to the use of fuzzy systems.
The obtaining of accurate but also human-comprehensible fuzzy systems played a key role …

This paper introduces a novel fuzzy rule-based classification method called FURIA, which is
short for Fuzzy Unordered Rule Induction Algorithm. FURIA extends the well-known RIPPER …

The inductive learning of fuzzy rule-based classification systems suffers from exponential
growth of the fuzzy rule search space when the number of patterns and/or variables …

Security policies of information systems and networks are designed for maintaining the
integrity of both the confidentiality and availability of the data for their trusted users …

The use of genetic algorithms for designing fuzzy systems provides them with the learning
and adaptation capabilities and is called genetic fuzzy systems (GFSs). This topic has …

This paper provides an in-depth review of the optimal design of type-1 and type-2 fuzzy
inference systems (FIS) using five well known computational frameworks: genetic-fuzzy …