Abstract The Proton Exchange Membrane Fuel Cell (PEMFC) air supply system takes on the
characteristics of external disturbances and uncertain parameters, which is difficult to …

This article proposes a new network approach toward the implementation of Takagi–Sugeno
(T–S) fuzzy models referred to as disjunctive fuzzy neural networks (DJFNNs). The proposed …

Fuzzy modeling has many advantages over nonfuzzy methods, such as robustness with
respect to uncertainties and less sensitivity to the varying dynamics of nonlinear systems …

In this study, we propose hierarchical polynomial-based fuzzy neural networks (HPFNN).
The aim of this study is to develop the design methodologies of hierarchical model to …

In this paper, a novel Bayesian Takagi-Sugeno-Kang (BTSK) fuzzy model and its joint
learning method BTSK-JL of structure identification and parameter estimation are proposed …

The COVID-19 pandemic has posed a significant global public health threat with an
escalating number of new cases and death toll daily. The early detection of COVID-related …

A data driven Fuzzy Inference System (FIS) employs Membership Functions (MFs) with
adjustable parameters in its IF part to fuzzify the input data. The input space is partitioned …

The number of fuzzy rules in a fuzzy neural network usually depends on the grid-type
partition or clustering-based partition. However, the number of grids or clusters needs to be …

Time series forecasting is an essential and challenging task, especially for large-scale time-
series (LSTS) forecasting, which plays a crucial role in many real-world applications. Due to …

Hierarchical TSK fuzzy system was proposed to approach the exponential growth of IF-
THEN rules which named “fuzzy rule explosion”. However, it could not get better …