Fungal infections are one of the main public health problems, especially in
immunocompromised patients, nosocomial environments, patients with chronic diseases …

In this article, we propose a new variant of evolving fuzzy model for regression problems,
which is based on error feedback integration in order to compensate measurement noise …

This chapter provides an all-round picture of the development and advances in the fields of
evolving fuzzy systems (EFS) and evolving neuro-fuzzy systems (ENFS) which have been …

Evolving classifiers and especially evolving fuzzy classifiers have been established as a
prominent technique for addressing the recent demands in building classifiers in an …

Interpretability in intelligent models becomes a challenge in academic research and
approaches that facilitate understanding the responses obtained in models based on …

Data stream classification processes with neuro-fuzzy approaches may involve situations
where uncertainties arise, which may directly interfere with the quality of the results of the …

Interpretable machine learning is trending as it aims to build a human-understandable
decision process. There are two main types of machine learning systems: white-box and …

Evolving classifiers and especially evolving fuzzy classifiers have been established as a
prominent technique for addressing the recent demands in building classifiers in an …

In this study, we present the operator-dependent sigmoid function, which is derived from a
universal unary operator called the kappa function. Here, we describe how the generalized …

In 2014, Hu introduced the concept of three-way decision spaces and axiomatic definition of
decision evaluation functions. In three-way decision spaces, decision evaluation function …