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

In this paper, a novel fuzzy neural network termed as dynamic parsimonious fuzzy neural
network (DPFNN) is proposed. DPFNN is a four layers network, which features coalescence …

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 …

There are two main approaches to design a neural fuzzy system; namely, through expert
knowledge, and through numerical data. While the computational structure of a system is …

As one of the three pillars in computational intelligence, fuzzy systems are a powerful
mathematical tool widely used for modelling nonlinear problems with uncertainties. Fuzzy …

Most of the dynamics in real-world systems are compiled by shifts and drifts, which are
uneasy to be overcome by omnipresent neuro-fuzzy systems. Nonetheless, learning in …

Adaptive neuro-fuzzy inference system (ANFIS) is efficient estimation model not only among
neuro-fuzzy systems but also various other machine learning techniques. Despite …

This paper presents a self-adaptive neuro-fuzzy inference system (SANFIS) that is capable
of self-adapting and self-organizing its internal structure to acquire a parsimonious rule-base …

This chapter provides a round picture of the development and advances in the field of
evolving fuzzy systems (EFS) made during the last decade since their first appearance in …

Fuzzy and neural-fuzzy systems have successfully and extensively applied to solve
problems in many research areas such as those associated with industrial, medical and …