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 …

This special issue explores big data analytics and applications for logistics and supply chain
management by examining novel methods, practices, and opportunities. The articles present …

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

The age of online data stream and dynamic environments results in the increasing demand
of advanced machine learning techniques to deal with concept drifts in large data streams …

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 …

Increasing demands on effluent quality and loads call for an improved control, monitoring,
and fault detection of waste-water treatment plants (WWTPs). Improved control and …

In this paper, we propose three criteria for efficient sample selection in case of data stream
regression problems within an online active learning context. The selection becomes …

Learning from data streams (incremental learning) is increasingly attracting research focus
due to many real-world streaming problems and due to many open challenges, among …

Notice of Violation of IEEE Publication Principles After careful consideration by a duly
constituted committee, an author of this article, Hamid Reza Karimi, was found to have acted …

We propose a new clustering method, which is dynamic in the sense that it updates its
structure (cluster partition) permanently based on new incoming data samples. As it …