Alzheimer's and related diseases are significant health issues of this era. The
interdisciplinary use of deep learning in this field has shown great promise and gathered …

The artificial electric field algorithm (AEFA) is a population-based metaheuristic optimization
algorithm. It is inspired by the electrostatic field theory and fundamental laws of physics. The …

Abstract The Marine Predators Algorithm (MPA) is a novel hunting-based optimizer. The
MPA's central concept is based on the well-known Lévy Flight (LF) and Brownian Motion …

Surface Electromyography (sEMG) is a technique for measuring muscle activity by recording
electrical signals from the surface of the body. It is widely used in fields such as medical …

In recent decades, there has been a surge in demand for the development of renewable
energies, leading to extensive research efforts focused on the gasification process …

This paper introduces a novel model for optimizing microgrid systems by integrating multi-
purpose renewable energy (MEM) and cutting-edge technologies, including electric vehicles …

With the scale and dimension of engineering optimization and real-world problems
increasing, it will be difficult to find the optimum solutions. This paper proposes a novel …

This paper introduces a novel approach that addresses the intricate challenges associated
with energy hubs, focusing on diverse issues in the transmission and production of energy …

This article introduces differentiated creative search (DCS), a groundbreaking optimization
algorithm that revolutionizes traditional decision-making systems in complex environments …

The knapsack problem with setup (KPS) is a combinatorial optimization problem with
important application in the industrial field. In order to solve KPS more quickly and effectively …