On Clustering Validation Techniques
Journal of Intelligent Information Systems
High performance genetic programming on GPU
BADS '09 Proceedings of the 2009 workshop on Bio-inspired algorithms for distributed systems
Density-based clustering using graphics processors
Proceedings of the 18th ACM conference on Information and knowledge management
A survey of evolutionary algorithms for clustering
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Accelerating large graph algorithms on the GPU using CUDA
HiPC'07 Proceedings of the 14th international conference on High performance computing
A SIMD interpreter for genetic programming on GPU graphics cards
EuroGP'08 Proceedings of the 11th European conference on Genetic programming
Proceedings of the 2nd workshop on Bio-inspired algorithms for distributed systems
An effective GPU implementation of breadth-first search
Proceedings of the 47th Design Automation Conference
Understanding of Internal Clustering Validation Measures
ICDM '10 Proceedings of the 2010 IEEE International Conference on Data Mining
Many-threaded implementation of differential evolution for the CUDA platform
Proceedings of the 13th annual conference on Genetic and evolutionary computation
Parallel density-based clustering of complex objects
PAKDD'06 Proceedings of the 10th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining
Parallel genetic algorithm on the CUDA architecture
EvoApplicatons'10 Proceedings of the 2010 international conference on Applications of Evolutionary Computation - Volume Part I
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Genetic and evolutionary algorithms have been used to find clusters in data with success. Unfortunately, evolutionary clustering suffers from the high computational costs when it comes to fitness function evaluation. The GPU computing is a recent programming and development paradigm introducing high performance parallel computing to general audience. This study presents a design, implementation, and evaluation of a genetic algorithm for density based clustering for the nVidia CUDA platform.