Image processing technology has always been a hot and difficult topic in the field of artificial
intelligence. With the rise and development of machine learning and deep learning …

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 …

Whale optimization algorithm (WOA) tends to fall into the local optimum and fails to converge
quickly in solving complex problems. To address the shortcomings, an improved WOA …

Intrusion Detection (ID) is an essential task in the cyberattacks domain built to secure
Internet applications and networks from malicious actors. The main shortcoming of the …

Datasets comprise a collection of features; however, not all of these features may be
necessary. Feature selection is the process of identifying the most relevant features while …

The paper addresses the limitations of the Moth-Flame Optimization (MFO) algorithm, a meta-
heuristic used to solve optimization problems. The MFO algorithm, which employs moths' …

Like most metaheuristic algorithms, salp swarm algorithm (SSA) suffers from slow
convergence and stagnation in the local optima. The study develops a novel Time-Based …

Salp swarm algorithm (SSA) is a unique swarm intelligent algorithm widely used for various
practical applications due to its simple framework and good optimization performance …

We present a bee foraging behavior-driven mutational salp swarm algorithm (BMSSA)
based on an improved bee foraging strategy and an unscented mutation strategy. The …

The Salp Swarm Algorithm (SSA) outperforms well-known algorithms such as particle swarm
optimizers and grey wolf optimizers in complex optimization challenges. However, like most …