During the past decade, solving complex optimization problems with metaheuristic
algorithms has received considerable attention among practitioners and researchers …

Feature selection has been widely used in data mining and machine learning tasks to make
a model with a small number of features which improves the classifier's accuracy. In this …

Feature selection plays a key role in reducing the dimensionality of a feature vector by
discarding redundant and irrelevant ones. In this paper, a Genetic Algorithm-based …

In this paper, optimal thresholds for multi-level thresholding in an image are obtained by
maximizing the Tsallis entropy using cuckoo search algorithm. The method is considered as …

This paper presents a novel adaptive cuckoo search (ACS) algorithm for optimization. The
step size is made adaptive from the knowledge of its fitness function value and its current …

Background In the last few years, multi-omics data, that is, datasets containing different types
of high-dimensional molecular variables for the same samples, have become increasingly …

Differential evolution has started to attract a lot of attention as a powerful search method and
has been successfully applied to a variety of applications including pattern recognition. One …

This paper introduces a two step algorithm for fault diagnosis of power transformers (2-
ADOPT) using a binary version of the multi-objective particle swarm optimization (MOPSO) …

Abstract The Internet of Things (IoT) makes IoT devices more vulnerable to cyberattacks,
especially Distributed Denial of Service (DDoS), raising privacy and security issues …

An increased number of bio-inspired face recognition systems have emerged in recent
decades owing to their intelligent problem-solving ability, flexibility, scalability, and adaptive …