In this paper a concise overview of the work that has been done by various researchers in
the area of type-2 fuzzy logic is analyzed and discussed. Type-2 fuzzy systems have been …

Neuro-fuzzy systems have attracted the growing interest of researchers in various scientific
and engineering areas due to its effective learning and reasoning capabilities. The neuro …

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 …

In this paper, to compute the firing strength values of type-2 fuzzy models, a soft version of
minimum is presented, which endows the fuzzy model with the ability to solve large …

Interval type-2 fuzzy neural networks (IT2FNNs) can be seen as the hybridization of interval
type-2 fuzzy systems (IT2FSs) and neural networks (NNs). Thus, they naturally inherit the …

In this paper a review of type-2 fuzzy logic applications in pattern recognition, classification
and clustering problems is presented. Recently, type-2 fuzzy logic has gained popularity in a …

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 …

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 …

Type-1 fuzzy sets can model the linguistic uncertainty from a single user, ie, intra-personal
uncertainty. Type-1 fuzzy systems have been widely used in controls and machine learning …

This paper presents a novel recurrent fuzzy neural network, called an interactively recurrent
self-evolving fuzzy neural network (IRSFNN), for prediction and identification of dynamic …