[HTML][HTML] Differential evolution: A recent review based on state-of-the-art works
Differential evolution (DE) is a popular evolutionary algorithm inspired by Darwin's theory of
evolution and has been studied extensively to solve different areas of optimisation and …
evolution and has been studied extensively to solve different areas of optimisation and …
Enhanced whale optimization algorithm for medical feature selection: A COVID-19 case study
The whale optimization algorithm (WOA) is a prominent problem solver which is broadly
applied to solve NP-hard problems such as feature selection. However, it and most of its …
applied to solve NP-hard problems such as feature selection. However, it and most of its …
Feature selection using bare-bones particle swarm optimization with mutual information
X Song, Y Zhang, D Gong, X Sun - Pattern Recognition, 2021 - Elsevier
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 …
data mining. Due to not considering characteristics of the FS problem itself, traditional …
Gene selection for microarray data classification based on Gray Wolf Optimizer enhanced with TRIZ-inspired operators
DNA microarray technology is the fabrication of a single chip to contain a thousand genetic
codes. Each microarray experiment can analyze many thousands of genes in parallel. The …
codes. Each microarray experiment can analyze many thousands of genes in parallel. The …
A robust algorithm based on differential evolution with local search for the capacitated vehicle routing problem
IP Souza, MCS Boeres, REN Moraes - Swarm and Evolutionary …, 2023 - Elsevier
Abstract The Capacitated Vehicle Routing Problem is a well-known combinatorial problem.
In this paper, we propose a hybrid algorithm based on a discrete adaptation of the …
In this paper, we propose a hybrid algorithm based on a discrete adaptation of the …
An adaptive hybrid mutated differential evolution feature selection method for low and high-dimensional medical datasets
Feature selection (FS) constitutes a crucial endeavor in classification procedures, aiming to
identify the minimal subset of features that maximizes classification accuracy. In the realm of …
identify the minimal subset of features that maximizes classification accuracy. In the realm of …
A constrained competitive swarm optimizer with an SVM-based surrogate model for feature selection
Feature selection (FS) is an important data preprocessing technique that selects a small
subset of relevant features to improve learning performance. However, it is also challenging …
subset of relevant features to improve learning performance. However, it is also challenging …
Differential Evolution with perturbation mechanism and covariance matrix based stagnation indicator for numerical optimization
Differential Evolution (DE), as a promising population-based stochastic optimization
algorithm, has drawn attention from researchers of various fields owing to its simple …
algorithm, has drawn attention from researchers of various fields owing to its simple …
Differential evolution based on network structure for feature selection
With the accumulation of high-dimensional data, feature selection (FS) plays a significant
role in tasks such as classification and clustering. Recently, many evolutionary algorithms …
role in tasks such as classification and clustering. Recently, many evolutionary algorithms …
An improved feature selection method based on angle-guided multi-objective PSO and feature-label mutual information
F Han, T Wang, Q Ling - Applied Intelligence, 2023 - Springer
Multi-objective particle swarm optimization (MOPSO) has been widely applied to feature
selection. Although these MOPSO-based feature selection methods have achieved good …
selection. Although these MOPSO-based feature selection methods have achieved good …