Data, as being the vital input of system modelling, contain dissimilar level of imprecision that
necessitates different modelling approaches for proper analysis of the systems. Numbers …

We present an application of type-2 neuro-fuzzy modeling to stock price prediction based on
a given set of training data. Type-2 fuzzy rules can be generated automatically by a self …

There is currently lot of work in ambient intelligence particularly in context awareness.
Context awareness enables service discovery and adaptation of computing devices for …

Abstract Type-2 fuzzy sets (T2FSs) can deal with higher modeling and uncertainties which
exist in the real-world application, specifically in the control systems. Particularly the climate …

Predicting stock prices with traditional time series analysis has proven to be difficult. Fuzzy
models have recently been used to predict stock market prices because they are capable of …

Challenging modeling problems include how to obtain a simple and accurate model for a
partial differential equation (PDE) unknown nonlinear distributed parameter system (DPS) …

Type‐2 (T2) fuzzy set was introduced to model vagueness associated with primary
membership function of type‐1 (T1) fuzzy set. While it was invented to handle more fuzzy …

Methods of qualitative analysis, such as qualitative classification, have gained importance
as an essential complement of existing quantitative analysis in numerous fields. Only a few …

Underground economy (UE) is known as hidden economy or shadow economy referring to
unpaid tax. We applied interval type-2 fuzzy logic system (IT2 FLS) model in measuring the …

In this paper, a modified interval type-2 fuzzy TS modeling method is applied to a heat
exchange process on the equipment CE117 Process Trainer. First, subtractive clustering …