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 …

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 …

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 …

This paper proposes the use of fuzzification functions based on clustering of data based on
their density to perform the granularization of the input space. The neurons formed in this …

Abstract Aspects of Autistic Spectrum Disorder (ASD) can be diagnosed, with rare frequency,
in people already in adulthood. To aid in the diagnosed of autistic traits, a mobile system …

The fuzzy neural networks are hybrid structures that can act in several contexts of the pattern
classification, including the detection of failures and anomalous behaviors. This paper …

The challenge of reducing complexity, failures and time in software development are tasks
found in the vast majority of information technology companies. The professionals seek to …

The growth of the computerization of processes and services has changed human relations
and, as a consequence, have created new forms of attacks and frauds for users of digital …

Neural network approaches are machine learning methods that are widely used in various
domains, such as healthcare and cybersecurity. Neural networks are especially renowned …

Human papillomavirus (HPV) infection is related to frequent cases of cervical cancer and
genital condyloma in humans. Up to now, numerous methods have come into existence for …