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 …

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 …

The existing uncertainties during the operation of processes could strongly affect the
performance of forecasting systems, control strategies and fault detection systems when they …

Many of decision-making and policy planning processes involve a time-series prediction
problem and so this area has extensive literature including a great variety of time-series …

There are various studies in which a variety of prediction tools have been introduced in time-
series prediction literature. Non-probabilistic approaches which are based on fuzzy set …

Extensive research results of stock market time series using classical fuzzy sets (type‐1) are
available in the literature. However, type‐1 fuzzy sets cannot fully capture the uncertainty …

Although adaptive network fuzzy inference system and fuzzy functions approach can be
utilized as a prediction tool, they have been not designed for prediction problem and they …

This paper presents an interval type-2 mutual subsethood fuzzy neural inference system
(IT2MSFuNIS). A mutual subsethood measure between two interval type-2 fuzzy sets (IT2 …

In the paper, trapezoidal type-2 fuzzy inference system (TT2FIS) is introduced. To construct
the type-2 fuzzy inference system, trapezoidal type-2 fuzzy sets are adopted to construct the …

This paper aims to design a self-evolving function-link type-2 fuzzy neural network for
application in controlling antilock braking systems. In this control scheme, the self-evolving …