Automatic clustering algorithms: a systematic review and bibliometric analysis of relevant literature

AE Ezugwu, AK Shukla, MB Agbaje… - Neural Computing and …, 2021 - Springer
Cluster analysis is an essential tool in data mining. Several clustering algorithms have been
proposed and implemented, most of which are able to find good quality clustering results …

Swarm intelligence for clustering—A systematic review with new perspectives on data mining

E Figueiredo, M Macedo, HV Siqueira… - … Applications of Artificial …, 2019 - Elsevier
The increase in available data has attracted the interest in clustering approaches as a way
of coherently aggregating them and identify patterns in big data. Hence, Swarm Intelligence …

Golden ball: a novel meta-heuristic to solve combinatorial optimization problems based on soccer concepts

E Osaba, F Diaz, E Onieva - Applied intelligence, 2014 - Springer
In this paper, a new multiple population based meta-heuristic to solve combinatorial
optimization problems is introduced. This meta-heuristic is called Golden Ball (GB), and it is …

A novel combinatorial merge-split approach for automatic clustering using imperialist competitive algorithm

Z Aliniya, SA Mirroshandel - Expert Systems with Applications, 2019 - Elsevier
Cluster analysis has a wide application in many areas, including pattern recognition,
information retrieval, and image processing. In most real-world clustering problems, the …

Nature-inspired metaheuristic techniques for automatic clustering: a survey and performance study

AE Ezugwu - SN Applied Sciences, 2020 - Springer
The application of several swarm intelligence and evolutionary metaheuristic algorithms in
data clustering problems has in the past few decades gained wide popularity and …

A comparative performance study of hybrid firefly algorithms for automatic data clustering

AES Ezugwu, MB Agbaje, N Aljojo, R Els… - IEEE …, 2020 - ieeexplore.ieee.org
In cluster analysis, the goal has always been to extemporize the best possible means of
automatically determining the number of clusters. However, because of lack of prior domain …

Automatic data clustering based on hybrid atom search optimization and sine-cosine algorithm

M Abd Elaziz, N Nabil, AA Ewees… - 2019 IEEE congress on …, 2019 - ieeexplore.ieee.org
Automatic clustering based hybrid metaheuristic algorithms has attracted the center of
interest of scientists and engineers which become a hot topic for different data analysis …

A modified genetic algorithm for forecasting fuzzy time series

E Bas, VR Uslu, U Yolcu, E Egrioglu - Applied intelligence, 2014 - Springer
Fuzzy time series approaches are used when observations of time series contain
uncertainty. Moreover, these approaches do not require the assumptions needed for …

Automatic cluster evolution using gravitational search algorithm and its application on image segmentation

V Kumar, JK Chhabra, D Kumar - Engineering Applications of Artificial …, 2014 - Elsevier
In real life problems, prior information about the number of clusters is not known. In this
paper, an attempt has been made to determine the number of clusters using automatic …

CDEPSO: a bi-population hybrid approach for dynamic optimization problems

JK Kordestani, A Rezvanian, MR Meybodi - Applied intelligence, 2014 - Springer
Many real-world optimization problems are dynamic, in which the environment, ie the
objective function and restrictions, can change over time. In this case, the optimal solution (s) …