Efficient strategies to contain the coronavirus disease 2019 (COVID-19) pandemic are
peremptory to relieve the negatively impacted public health and global economy, with the …

We analyze a plurality of epidemiological models through the lens of physics-informed
neural networks (PINNs) that enable us to identify time-dependent parameters and data …

This paper comprehensively studies effective numerical methods for solving the simplest
chaotic circuit model. We introduce a novel scheme for the Atangana–Baleanu Caputo …

Wireless sensor networks (WSNs) are subject to cyber attacks. Security of such networks is a
significant priority for everyone. Due to the network's frail defense mechanisms, WSNs are …

Complex systems widely exist in nature and human society. There are complex interactions
between system elements in a complex system, and systems show complex features at the …

Modeling human behavior within mathematical models of infectious diseases is a key
component to understand and control disease spread. We present a mathematical …

The paper aims to utilize an integral transform, specifically the Khalouta transform, an
abstraction of various integral transforms, to address fractional differential equations using …

In this work, we present a new type of fractional derivatives (FD) involving exponential
cotangent function in their kernels called Riemann–Liouville D σ, γ and Caputo cotangent …

Human interactions and perceptions about health risk are essential to understand the
evolution over the course of a pandemic. We present a Susceptible-Exposed-Asymptomatic …

In view of the facts in the infection and propagation of COVID-19, a stochastic reaction–
diffusion epidemic model is presented to analyse and control this infectious diseases …