The main objective of feature selection is to improve learning performance by selecting
concise and informative feature subsets, which presents a challenging task for machine …

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

Humans take immense pride in their ability to be unpredictably intelligent and despite huge
advances in science over the past century; our understanding about human brain is still far …

Evaluating the PV system parameters is crucial for the more efficient utilization of
sustainable solar energy. Due to PV systems' nonlinear and multimodal nature, efficient …

For years, extensive research has been in the binarization of continuous metaheuristics for
solving binary-domain combinatorial problems. This paper is a continuation of a previous …

Proposing a reliable feature selection approach is the primary stone for endorsing the
prediction performance; therefore, this paper proposes an enhanced optimization technique …

Feature selection is becoming a relevant problem within the field of machine learning. The
feature selection problem focuses on the selection of the small, necessary, and sufficient …

As one novel meta-heuristic algorithm, African Vultures Optimization Algorithm (AVOA) has
been proved to be efficient in solving continuous optimization problems. However, many real …

This paper proposes a novel hybrid optimization algorithm named GPOFWA, which
integrates political optimizer (PO) with fireworks algorithm (FWA) to solve numerical and …

Political Optimizer (PO) is a recently proposed meta-heuristic with excellent convergence
speed and exploitation capability. However, it is found that PO prematurely converges for …