The problem of concept drift has gained a lot of attention in recent years. This aspect is key
in many domains exhibiting non-stationary as well as cyclic patterns and structural breaks …

This paper provides an in-depth review of the optimal design of type-1 and type-2 fuzzy
inference systems (FIS) using five well known computational frameworks: genetic-fuzzy …

Recent advances in computational intelligent systems have focused on addressing complex
problems related to the dynamicity of the environments. In increasing number of real world …

This overview gravitates on research achievements that have recently emerged from the
confluence between Big Data technologies and bio-inspired computation. A manifold of …

Fuzzy rule-based systems (FRBSs) is a rule-based system which uses linguistic fuzzy
variables as antecedents and consequent to represent human-understandable knowledge …

Identification of models from input-output data essentially requires estimation of appropriate
cluster centers. In this paper, a new online evolving clustering approach for streaming data …

A new on-line evolving clustering approach for streaming data is proposed in this paper. The
approach is based on the concept that local mean of samples within a region has the …

Evolvable Takagi-Sugeno (TS) models are fuzzy-rule-based models with the ability to
continuously learn and adapt to incoming samples from data streams. The model adjusts …

In recent years, the problem of concept drift has gained importance in the financial domain.
The succession of manias, panics and crashes have stressed the non-stationary nature and …

Recent crises, recessions and bubbles have stressed the non-stationary nature and the
presence of drastic structural changes in the financial domain. The most recent literature …