Кластеризація векторних та матричних масивів даних із використанням комбінованого еволюційного методу рибних зграй

The problem of clustering data arrays described in both vector and matrix forms and based on the optimization of data distribution density functions in these arrays is considered. For the optimization of these functions, the algorithm that is a hybrid of Fish School Search, random search, and evolut...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Datum:2022
Hauptverfasser: Bodyanskiy, Yevgeniy, Shafronenko, Alina, Pliss, Iryna
Format: Artikel
Sprache:Englisch
Veröffentlicht: The National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute" 2022
Schlagworte:
Online Zugang:http://journal.iasa.kpi.ua/article/view/275083
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Назва журналу:System research and information technologies

Institution

System research and information technologies
Beschreibung
Zusammenfassung:The problem of clustering data arrays described in both vector and matrix forms and based on the optimization of data distribution density functions in these arrays is considered. For the optimization of these functions, the algorithm that is a hybrid of Fish School Search, random search, and evolutionary optimization is proposed. This algorithm does not require calculating the optimized function’s derivatives and, in the general case, is designed to find optimums of multiextremal functions of the matrix argument (images). The proposed approach reduces the number of runs of the optimization procedure, finds extrema of complex functions with many extrema, and is simple in numerical implementation.