In search of optimal clusters using genetic algorithms
Pattern Recognition Letters
`` Direct Search'' Solution of Numerical and Statistical Problems
Journal of the ACM (JACM)
An evolutionary technique based on K-means algorithm for optimal clustering in RN
Information Sciences—Applications: An International Journal
Differential evolution and particle swarm optimisation in partitional clustering
Computational Statistics & Data Analysis
K-Means-Type Algorithms: A Generalized Convergence Theorem and Characterization of Local Optimality
IEEE Transactions on Pattern Analysis and Machine Intelligence
Hybrid methods using genetic algorithms for global optimization
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
A hybrid approach to modeling metabolic systems using a geneticalgorithm and simplex method
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Selective regenerated particle swarm optimization for multimodal function
ACS'08 Proceedings of the 8th conference on Applied computer scince
Learning and Intelligent Optimization
A particle swarm with selective particle regeneration for multimodal functions
WSEAS Transactions on Information Science and Applications
An efficient hybrid data clustering method based on K-harmonic means and Particle Swarm Optimization
Expert Systems with Applications: An International Journal
A CBR-based fuzzy decision tree approach for database classification
Expert Systems with Applications: An International Journal
An efficient hybrid approach based on PSO, ACO and k-means for cluster analysis
Applied Soft Computing
Comparative clustering analysis of bispectral index series of brain activity
Expert Systems with Applications: An International Journal
A hybrid approach for supplier cluster analysis
Computers & Mathematics with Applications
An artificial bee colony approach for clustering
Expert Systems with Applications: An International Journal
A new clustering algorithm based on PSO with the jumping mechanism of SA
IITA'09 Proceedings of the 3rd international conference on Intelligent information technology application
Ant clustering algorithm with K-harmonic means clustering
Expert Systems with Applications: An International Journal
Chaotic maps based on binary particle swarm optimization for feature selection
Applied Soft Computing
Engineering Applications of Artificial Intelligence
Particle swarm optimization with selective particle regeneration for data clustering
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
A clustering based approach for skyline diversity
Expert Systems with Applications: An International Journal
A novel hybrid K-harmonic means and gravitational search algorithm approach for clustering
Expert Systems with Applications: An International Journal
A new hybrid method based on partitioning-based DBSCAN and ant clustering
Expert Systems with Applications: An International Journal
A review on particle swarm optimization algorithms and their applications to data clustering
Artificial Intelligence Review
A survey: hybrid evolutionary algorithms for cluster analysis
Artificial Intelligence Review
Review: A particle swarm optimization approach to clustering
Expert Systems with Applications: An International Journal
Application of gravitational search algorithm on data clustering
RSKT'11 Proceedings of the 6th international conference on Rough sets and knowledge technology
Expert Systems with Applications: An International Journal
Engineering Applications of Artificial Intelligence
Color quantization using modified artificial fish swarm algorithm
AI'11 Proceedings of the 24th international conference on Advances in Artificial Intelligence
Chaotic particle swarm optimization for data clustering
Expert Systems with Applications: An International Journal
Automatic fuzzy decision making system with learning for competing and connected businesses
Expert Systems with Applications: An International Journal
In search of optimal centroids on data clustering using a binary search algorithm
Pattern Recognition Letters
Data clustering using hybrid particle swarm optimization
IDEAL'12 Proceedings of the 13th international conference on Intelligent Data Engineering and Automated Learning
Dynamic clustering using combinatorial particle swarm optimization
Applied Intelligence
Hi-index | 12.07 |
Data clustering helps one discern the structure of and simplify the complexity of massive quantities of data. It is a common technique for statistical data analysis and is used in many fields, including machine learning, data mining, pattern recognition, image analysis, and bioinformatics, in which the distribution of information can be of any size and shape. The well-known K-means algorithm, which has been successfully applied to many practical clustering problems, suffers from several drawbacks due to its choice of initializations. A hybrid technique based on combining the K-means algorithm, Nelder-Mead simplex search, and particle swarm optimization, called K-NM-PSO, is proposed in this research. The K-NM-PSO searches for cluster centers of an arbitrary data set as does the K-means algorithm, but it can effectively and efficiently find the global optima. The new K-NM-PSO algorithm is tested on nine data sets, and its performance is compared with those of PSO, NM-PSO, K-PSO and K-means clustering. Results show that K-NM-PSO is both robust and suitable for handling data clustering.