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 …

Evolving systems unfolds from the interaction and cooperation between systems with
adaptive structures, and recursive methods of machine learning. They construct models and …

Major assumptions in computational intelligence and machine learning consist of the
availability of a historical dataset for model development, and that the resulting model will, to …

A self-organizing algorithm based on an online cluster and fuzzy sets update algorithm
(OCFU) and fuzzy-classification-based social learning particle swarm optimization (FC …

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 …

In this investigation, a model free discrete time neural network control is designed for the
trajectory tracking of a kind of nonlinear processes. The introduced control has three main …

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 …

Fuzzy control has become one of the most effective tools for dealing with complex
engineering processes. Over the years, research on fuzzy control systems has continuously …

The aim of this research is to revise and substantially extend experimental modelling and
control of a looped heating-cooling laboratory process with long input-output and internal …

This paper presents an evolving cloud-based algorithm for the recognition of drivers' actions.
The general idea is to detect different manoeuvres by processing the standard signals that …