Add to ORKGIn the past decade, various clustering algorithms based on the behaviour of real ants were proposed. The main advantage of these algorithms lies in the fact that no additional information, such as an initial partitioning of the data or the number of clusters, is needed. In this paper we show how the combination of the ant-based approach with fuzzy rules leads to an algorithm which is conceptually simpler, more efficient and more robust than previous approaches
This Thesis is brought to you for free and open access by the Graduate School at Scholar Commons. It...
Ant-based clustering and sorting is a nature-inspired heuristic for general clustering tasks. It ha...
This paper presents an ant colony optimization methodology for optimally clustering N objects into K...
In the past decade, various clustering algorithms based on the behaviour of real ants were proposed....
This paper provides a new intelligent technique for semisupervised data clustering problem that comb...
We present two Swarm Intelligence based approaches for data clustering. The first algorithm, Fuzzy A...
Clustering is actively used in several research fields, such as pattern recognition, machine learnin...
Algorithms for clustering web search results have to be efficient and robust. Furthermore they must ...
Algorithms for clustering Web search results have to be efficient and robust. Furthermore they must...
International audience For many examples of social insect metaphor for solving problems, several alg...
Wepresent in this paper a modification of Lumer and Faieta’s algorithm for data clustering. This app...
International audienceIn this paper is presented a new model for data clustering, which is inspired ...
This paper proposes fuzzy systems design by clustering-aided ant colony optimization (ACO) algorithm...
In this paper we will present a new clustering algorithm for unsupervised learning. It is inspired f...
Abstract — We introduce a new swarm intelligence based algorithm for data clustering with a kernel-i...
This Thesis is brought to you for free and open access by the Graduate School at Scholar Commons. It...
Ant-based clustering and sorting is a nature-inspired heuristic for general clustering tasks. It ha...
This paper presents an ant colony optimization methodology for optimally clustering N objects into K...
In the past decade, various clustering algorithms based on the behaviour of real ants were proposed....
This paper provides a new intelligent technique for semisupervised data clustering problem that comb...
We present two Swarm Intelligence based approaches for data clustering. The first algorithm, Fuzzy A...
Clustering is actively used in several research fields, such as pattern recognition, machine learnin...
Algorithms for clustering web search results have to be efficient and robust. Furthermore they must ...
Algorithms for clustering Web search results have to be efficient and robust. Furthermore they must...
International audience For many examples of social insect metaphor for solving problems, several alg...
Wepresent in this paper a modification of Lumer and Faieta’s algorithm for data clustering. This app...
International audienceIn this paper is presented a new model for data clustering, which is inspired ...
This paper proposes fuzzy systems design by clustering-aided ant colony optimization (ACO) algorithm...
In this paper we will present a new clustering algorithm for unsupervised learning. It is inspired f...
Abstract — We introduce a new swarm intelligence based algorithm for data clustering with a kernel-i...
This Thesis is brought to you for free and open access by the Graduate School at Scholar Commons. It...
Ant-based clustering and sorting is a nature-inspired heuristic for general clustering tasks. It ha...
This paper presents an ant colony optimization methodology for optimally clustering N objects into K...