Industrial Internet-of-Things (IIoT) are highly vulnerable to cyber-attacks due to their open
deployment in unattended environments. Intrusion detection is an efficient solution to …

In dynamic optimization problems (DOPs), as the environment changes through time, the
optima also dynamically change. How to adapt to the dynamic environment and quickly find …

We propose a neural network architecture that emulates the behavior of a physics solver that
solves electricity differential equations to compute electricity flow in power grids (so-called" …

Artificial intelligence (AI) is entering medical imaging, mainly enhancing image
reconstruction. Nevertheless, improvements throughout the entire processing, from signal …

In this article, the recursive filtering problem is investigated for a class of time-varying
complex networks with state saturations and random coupling strengths under an event …

Graph neural networks (GNNs) have emerged recently as a powerful architecture for
learning node and graph representations. Standard GNNs have the same expressive power …

Complex networks provide a powerful tool for data representation due to its ability to
describe the interplay between topological, functional, and dynamical properties of the input …

Abstract The Internet of Things (IoT), uses communication technologies and intelligent
computing to improve data analysis and computation accuracy, which is essential to the …

Takagi–Sugeno–Kang (TSK) fuzzy inference has been widely used in approximating
uncertain nonlinear systems because of its high interpretability and precision. However, TSK …

Link prediction in a graph is the problem of detecting the missing links or the ones that would
be formed in the near future. Using a graph representation of the data, we can convert the …