AI in finance refers to the applications of AI techniques in financial businesses. This area has
attracted attention for decades, with both classic and modern AI techniques applied to …

Deep neural networks (DNN) have remarkably progressed in applications involving large
and complex datasets but have been criticized as a black-box. This downside has recently …

Deep neuro-fuzzy systems (DNFSs) have been successfully applied to real-world problems
using the efficient learning process of deep neural networks (DNNs) and reasoning aptitude …

Human activity recognition has become a pillar of today intelligent Human–Computer
Interfaces as it typically provides more comfortable and ubiquitous interaction. This paper …

With excellent global approximation performance and interpretability, Takagi-Sugeno-Kang
(TSK) fuzzy systems have enjoyed a wide range of applications in various fields, such as …

Advancement and application of rule-based expert systems have been a key research area
in explainable artificial intelligence (XAI) because the rule-base is one of the most common …

The double-input-rule-modules stacked deep fuzzy method (DIRM-DFM) has attracted much
attention because of its interpretability and prediction accuracy. However, when confronted …

Wang–Mendel (WM) fuzzy system is an effective and interpretable model for solving tabular
data classification problem. However, original WM fuzzy system is weak in handling dataset …

Abstract Deep Neuro-Fuzzy System has been successfully employed in various
applications. But, the model faces two issues:(i) dataset with many features exponentially …

Accurate prediction of the photovoltaic (PV) power generation is of great significance for the
efficient management of the power grid. In order to strengthen the interpretability of the data …