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 …

With the rapid advancement in the battery industry, more accurate and advanced state
estimation methods are required to meet the performance requirements. The State of Health …

This paper formulates a fuzzy logic neuron that uses n-uninorms to construct uni-
nullneurons. A fuzzy neural network (FNN) composed of these neurons is easy to operate …

Research on predictions of breast cancer grows in the scientific community, providing data
on studies in patient surveys. Predictive models link areas of medicine and artificial …

This paper proposes a hybrid architecture based on neural networks, fuzzy systems, and n-
uninorms for solving pattern classification problems, termed as ENFS-Uni0 (short for …

This article proposes a new network approach toward the implementation of Takagi–Sugeno
(T–S) fuzzy models referred to as disjunctive fuzzy neural networks (DJFNNs). The proposed …

This paper proposes the definition of the architecture of an evolving fuzzy neural network
based on self-organizing direction aware data partitioning through stochastic processes …

Its constant technological evolution characterizes the contemporary world, and every day the
processes, once manual, become computerized. Data are stored in the cyberspace, and as …

The successful production of metallic workpieces through selective laser melting requires a
quality assurance process that can effectively and nondestructively assess internal defects …

Evolving fuzzy neural classifiers are incremental, adaptive models that use new samples to
update the architecture and parameters of the models with new incoming data samples …