The slime mould algorithm (SMA) is a population-based optimization algorithm that mimics
the foraging behavior of slime moulds with a simple structure and few hyperparameters …

Particle swarm optimization (PSO) is a popular heuristic method, which is capable of
effectively dealing with various optimization problems. A detailed overview of the original …

Abstract Intrusion Detection Systems (IDSs) have become essential to the sound operations
of networks. These systems have the potential to identify and report deviations from normal …

The selection of the mutation strategy for differential evolution (DE) algorithm plays an
important role in the optimization performance, such as exploration ability, convergence …

The “curse of dimensionality” and the high computational cost have still limited the
application of the evolutionary algorithm in high-dimensional feature selection (FS) …

Adam is an adaptive gradient descent approach that is commonly used in back-propagation
(BP) algorithms for training feed-forward neural networks (FFNNs). However, it has the …

Feature selection is an important data processing method to reduce dimension of the raw
datasets while preserving the information as much as possible. In this paper, an enhanced …

Feature selection (FS) is an important data pre-processing technique in classification. In
most cases, FS can improve classification accuracy and reduce feature dimension, so it can …

Feature selection (FS) is an important data processing method in pattern recognition and
data mining. Due to not considering characteristics of the FS problem itself, traditional …

Feature selection (FS) is an important data processing technique in the field of machine
learning. There have been various FS methods, but all assume that the cost associated with …