Selecting relevant feature subsets is vital in machine learning, and multiclass feature
selection is harder to perform since most classifications are binary. The feature selection …

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 …

The hybrid renewable energy system (HRES) has been presented as the most studied
solution for improving the sustainability of energy production infrastructures in isolated …

Structural engineering is focused on the safe and efficient design of infrastructure. Projects
can range in size and complexity, many requiring massive amounts of materials and …

Non-traditional optimization tools have proved their potential in solving various types of
optimization problems. These problems deal with either single objective or multiple/many …

In this study, the dandelion optimizer (DO) is examined for the optimum design of structures.
The results of the optimization process show that DO does not have good performance in the …

The current trend in global optimization research is to hybridize multiple variants to improve
the quality of solutions to real-world problems that have recently arisen in practise. This …

With the increase of communication devices and demands, the problems of high power
consumption, tight spectrum resources, and low energy efficiency in the two-layer …

Lithium-ion batteries are becoming more popular due to their superior performance like high
power density, long lifespan, broad operating range of temperatures, quick charging …

The existing slime mould algorithm clones the uniqueness of the phase of oscillation of
slime mould conduct and exhibits slow convergence in local search space due to poor …