Wszystkie pola: Ant Colony algorithm - Katalog OPAC zbiorów

Skocz do pozycji: 1.

Tytuł:: An ant algorithm for the maximum number of 3-cliques in 3-partite graphs
Autorzy:: Schiff, Krzysztof
Powiązania:: https://bibliotekanauki.pl/articles/2183443.pdf
Data publikacji:: 2021
Wydawca:: Polska Akademia Nauk. Instytut Badań Systemowych PAN
Tematy:: ant colony optimization
three-partite graph
3-clique
combinatorial optimization
graph theory
Opis:: The problem of finding the maximum number of d- vertices cliques (d = 3) in d-partite graph (d = 3) when graph density q is lower than 1 is an important problem in combinatorial optimization and it is one of many NP-complete problems. For this problem a meta-heuristic algorithm has been developed, namely an ant colony optimization algorithm. In this paper a new development of this ant algorithm and experimental results are presented. The problem of finding the maximum number of 3-vertices cliques can be encountered in computer image analysis, computer vision applications, automation and robotic vision systems. The optimal solution of this problem boils down to finding a set of 3-vertices cliques in a 3-partite graph and this set should have cardinality as high as possible. The elaborated ant colony algorithm can be easily modified for d-dimensional problems, that is for finding the maximum number of d-vertices cliques in a d-partite graph.
Źródło:: Control and Cybernetics; 2021, 50, 2; 347--358
0324-8569
Pojawia się w:: Control and Cybernetics
Dostawca treści:: Biblioteka Nauki

Artykuł

Skocz do pozycji: 2.

Tytuł:: Ant colony metaphor in a new clustering algorithm
Autorzy:: Boryczka, U.
Powiązania:: https://bibliotekanauki.pl/articles/969824.pdf
Data publikacji:: 2010
Wydawca:: Polska Akademia Nauk. Instytut Badań Systemowych PAN
Tematy:: data mining
cluster analysis
ant clustering algorithm
Opis:: Among the many bio-inspired techniques, ant clustering algorithms have received special attention, especially because they still require much investigation to improve performance, stability and other key features that would make such algorithms mature tools for data mining. Clustering with swarm-based algorithms is emerging as an alternative to more conventional clustering methods, such as k-means algorithm. This proposed approach mimics the clustering behavior observed in real ant colonies. As a case study, this paper focuses on the behavior of clustering procedures in this new approach. The proposed algorithm is evaluated on a number of well-known benchmark data sets. Empirical results clearly show that the ant clustering algorithm (ACA) performs well when compared to other techniques.
Źródło:: Control and Cybernetics; 2010, 39, 2; 343-358
0324-8569
Pojawia się w:: Control and Cybernetics
Dostawca treści:: Biblioteka Nauki

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