Recently, the numerical optimization field has attracted the research community to propose
and develop various metaheuristic optimization algorithms. This paper presents a new …

Multilevel Thresholding (MLT) is considered as a significant and imperative research field in
image segmentation that can efficiently resolve difficulties aroused while analyzing the …

The increased interest in renewable-based microgrids imposes several challenges, such as
source integration, power quality, and operating cost. Dealing with these problems requires …

In the recent era, Metaheuristic Algorithms (MHs) are developed to tackle many and different
optimization problems. The merit of the MHs is not only its simplicity to understand but also …

Optimization is the process of searching for the optimal (best-so-far) solution among a wide
range of solutions. Besides, in the last two decades, a family of algorithms known as …

In view of the shortcomings such as slow search speed, low optimization precision and
premature convergence of artificial hummingbird algorithm, an enhanced artificial …

Reducing pollutant emissions from electricity production in the power system positively
impacts the control of greenhouse gas emissions. Boosting kernel search optimizer (BKSO) …

Recently, the resources of renewable energy have been in intensive use due to their
environmental and technical merits. The identification of unknown parameters in …

The electrochemical parameter identification of Proton-exchange membrane fuel cells
(PEMFCs) is a highly nonlinear optimization problem. In this study, a new optimization …

Abstract The Internet of Medical Things (IoMT) ecosystem is enormous and complicated,
with several smart devices constantly transferring large amounts of data. Many IoT-based …