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 makes a systematic bibliographical analysis of the contributions of fuzzy set
theory (FST) on option pricing to state principal mainstream focuses and exposes the basic …

In this paper, we propose a new methodology for learning evolving fuzzy systems (EFS) from
data streams in terms of on-line regression/system identification problems. It comes with …

Nowadays, there is increasing demand for an integrated system usable to real-time
environments under limited computational resources and minimum operator supervision. In …

Heart disease is the leading cause of death among both men and women in most countries
in the world. Thus, people must be mindful of heart disease risk factors. Although genetics …

Fuzzy inference systems have been commonly used for time series forecasting in the
literature. Adaptive network fuzzy inference system, fuzzy time series approaches and fuzzy …

In this position paper, we are discussing achievements and open issues in the
interpretability of evolving fuzzy systems (EFS). In addition to pure on-line complexity …

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 …

As a paradigm of data processing, granular computation concerns processing complex data
entities called granules, which arise from data abstraction and derivation of knowledge from …

This paper suggests a synergy of fuzzy logic and nature-inspired optimization in terms of the
nature-inspired optimal tuning of the input membership functions of a class of Takagi …