Particle swarm optimisation: a historical review up to the current developments

D Freitas, LG Lopes, F Morgado-Dias - Entropy, 2020 - mdpi.com
The Particle Swarm Optimisation (PSO) algorithm was inspired by the social and biological
behaviour of bird flocks searching for food sources. In this nature-based algorithm …

Chemometric methods in data processing of mass spectrometry-based metabolomics: A review

L Yi, N Dong, Y Yun, B Deng, D Ren, S Liu… - Analytica chimica acta, 2016 - Elsevier
This review focuses on recent and potential advances in chemometric methods in relation to
data processing in metabolomics, especially for data generated from mass spectrometric …

A survey on swarm intelligence approaches to feature selection in data mining

BH Nguyen, B Xue, M Zhang - Swarm and Evolutionary Computation, 2020 - Elsevier
One of the major problems in Big Data is a large number of features or dimensions, which
causes the issue of “the curse of dimensionality” when applying machine learning …

A survey on evolutionary computation approaches to feature selection

B Xue, M Zhang, WN Browne… - IEEE Transactions on …, 2015 - ieeexplore.ieee.org
Feature selection is an important task in data mining and machine learning to reduce the
dimensionality of the data and increase the performance of an algorithm, such as a …

A survey on feature selection methods

G Chandrashekar, F Sahin - Computers & electrical engineering, 2014 - Elsevier
Plenty of feature selection methods are available in literature due to the availability of data
with hundreds of variables leading to data with very high dimension. Feature selection …

A GA-LR wrapper approach for feature selection in network intrusion detection

C Khammassi, S Krichen - computers & security, 2017 - Elsevier
Intrusions constitute one of the main issues in computer network security. Through malicious
actions, hackers can have unauthorised access that compromises the integrity, the …

Particle swarm optimisation for feature selection in classification: Novel initialisation and updating mechanisms

B Xue, M Zhang, WN Browne - Applied soft computing, 2014 - Elsevier
In classification, feature selection is an important data pre-processing technique, but it is a
difficult problem due mainly to the large search space. Particle swarm optimisation (PSO) is …

A novel hybrid genetic algorithm with granular information for feature selection and optimization

H Dong, T Li, R Ding, J Sun - Applied Soft Computing, 2018 - Elsevier
Feature selection has been a significant task for data mining and pattern recognition. It aims
to choose the optimal feature subset with the minimum redundancy and the maximum …

A hybrid barnacles mating optimizer algorithm with support vector machines for gene selection of microarray cancer classification

EH Houssein, DS Abdelminaam, HN Hassan… - IEEE …, 2021 - ieeexplore.ieee.org
These days, the classification between normal and cancerous tissues and between different
types of cancers represents a very important issue. Selecting the little informative number of …

Modified binary PSO for feature selection using SVM applied to mortality prediction of septic patients

SM Vieira, LF Mendonça, GJ Farinha… - Applied Soft Computing, 2013 - Elsevier
This paper proposes a modified binary particle swarm optimization (MBPSO) method for
feature selection with the simultaneous optimization of SVM kernel parameter setting …